JAVA IEEE

Modeling and Detection of Camouflaging Worm (2011)

ABSTRACT
Active worms pose major security threats to the Internet. This is due to the ability of active worms to propagate in an automated fashion as they continuously compromise computers on the Internet. Active worms evolve during their propagation and thus pose great challenges to defend against them. In this paper, we investigate a new class of active worms, referred to as Camouflaging Worm (C-Worm in short). The C-Worm is different from traditional worms because of its ability to intelligently manipulate its scan traffic volume over time. Thereby, the C-Worm camouflages its propagation from existing worm detection systems based on analyzing the propagation traffic generated by worms. We analyze characteristics of the C-Worm and conduct a comprehensive comparison between its traffic and non-worm traffic (background traffic). We observe that these two types of traffic are barely distinguishable in the time domain. However, their distinction is clear in the frequency domain, due to the recurring manipulative nature of the C-Worm. Motivated by our observations, we design a novel spectrum-based scheme to detect the C-Worm. Our scheme uses the Power Spectral Density (PSD) distribution of the scan traffic volume and its corresponding Spectral Flatness Measure (SFM) to distinguish the C-Worm traffic from background traffic. Using a comprehensive set of detection metrics and real-world traces as background traffic, we conduct extensive performance evaluations on our proposed spectrum-based detection scheme. The performance data clearly demonstrates that our scheme can effectively detect the C-Worm propagation. Furthermore, we show the generality of our spectrum-based scheme in effectively detecting not only the C-Worm, but traditional worms as well


     

Online Intrusion Alert Aggregation With Generative Data Stream Modeling (2011)

ABSTRACT
Alert aggregation is an important subtask of intrusion detection. The goal is to identify and to cluster different alerts—produced by low-level intrusion detection systems, firewalls, etc.—belonging to a specific attack instance which has been initiated by an attacker at a certain point in time. Thus, meta-alerts can be generated for the clusters that contain all the relevant information whereas the amount of data (i.e., alerts) can be reduced substantially. Meta-alerts may then be the basis for reporting to security experts or for communication within a distributed intrusion detection system. We propose a novel technique for online alert aggregation which is based on a dynamic, probabilistic model of the current attack situation. Basically, it can be regarded as a data stream version of a maximum likelihood approach for the estimation of the model parameters. With three benchmark data sets, we demonstrate that it is possible to achieve reduction rates of up to 99.96 percent while the number of missing meta-alerts is extremely low. In addition, meta-alerts are generated with a delay of typically only a few seconds after observing the first alert belonging to a new attack instance
     

A Competitive Study of Cryptography Techniques over Block Cipher  (2011)

ABSTRACT
The complexity of cryptography does not allow many people to actually understand the motivations and therefore available for practicing security cryptography. Cryptography process seeks to distribute an estimation of basic cryptographic primitives across a number of confluences in order to reduce security assumptions on individual nodes, which establish a level of fault-tolerance opposing to the node alteration. In a progressively networked and distributed communications environment, there are more and more useful situations where the ability to distribute a computation between a number of unlike network intersections is needed. The reason back to the efficiency (separate nodes perform distinct tasks), fault-tolerance (if some nodes are unavailable then others can perform the task) and security (the trust required to perform the task is shared between nodes) that order differently. Hence, this paper aims to describe and review the different research that has done toward text encryption and description in the block cipher. Moreover, this paper suggests a cryptography model in the block cipher.


     

Secure Data Collection in Wireless Sensor Networks Using Random Routing Algorithms (2011)

ABSTRACT
Wireless Sensor Networks make it possible to send secure data from source to estimation. If applied to network monitoring data on a host, they can used to detect compromised node and denial-of-service is two key attacks. In this paper, we present four "Multi-path randomized routing Algorithm" a method to send the data multiple ways to classify the data in to normal and attacks in wireless sensor networks. The Pure Random Propagation shares are propagated based on one-hop neighborhood information, sink TTL initial value N in each share and remaining algorithms improve the efficiency of shares based on using two-hop neighborhood information. Our work studies the best algorithm by detecting the comprised nodes with black holes and denial of service in the packet information with Multipath routing algorithms that has not been used before. We analyses the algorithm that have the best efficiency and describes the proposed system


     

A Cross layer architecture for multicast and unicast video transmission in mobile broadband networks (2011)

ABSTRACT
This paper focuses on the transport of Unicast and Multicast traffic in the mobile broadband networks. The main objective is to allow video streaming applications to adapt its parameters according to 802.16MAC layer conditions and resource availability. For unicast traffic, we propose a cross layer optimizer, named XLO, between scalable video streaming application and IEEE 802.16 MAC layer. XLO uses the existing service flow management messages exchanged between a base station (BS) and a subscriber station (SS) and make them available to the video streaming application via a specific XLO interface. We implemented the XLO in the QualNet simulator and performed extensive simulations using a personalized scalable video traffic generator, capable of streaming video with different data rates and quality levels. We also introduce an enhanced admission control function at the BS that takes into account video adaptability property. The simulation results show the effectiveness of our XLO mechanism for delivering better quality of service. For multicast traffic, we propose a new solution based on superposition coding and make use of scalable video coding in order to optimize the network resources


     

A New Approach for FEC Decoding Based on the BP Algorithm in LTE and WiMAX Systems  (2011)

ABSTRACT
Many wireless communication systems such as IS- 54, enhanced data rates for the GSM evolution (EDGE), worldwide interoperability for microwave access (WiMAX) and long term evolution (LTE) have adopted low-density parity-check (LDPC), tail-biting convolutional, and turbo codes as the forward error correcting codes (FEC) scheme for data and overhead channels. Therefore, many efficient algorithms have been proposed for decoding these codes. However, the different decoding approaches for these two families of codes usually lead to different hardware architectures. Since these codes work side by side in these new wireless systems, it is a good idea to introduce a universal decoder to handle these two families of codes. The present work exploits the parity-check matrix (H) representation of tailbiting convolutional and turbo codes, thus enabling decoding via a unified belief propagation (BP) algorithm. Indeed, the BP algorithm provides a highly effective general methodology for devising low-complexity iterative decoding algorithms for all convolutional code classes as well as turbo codes. While a small performance loss is observed when decoding turbo codes with BP instead of MAP, this is offset by the lower complexity of the BP algorithm and the inherent advantage of a unified decoding architecture.


     

Enhancing Privacy and Authorization Control Scalability in the Grid  (2009)

ABSTRACT
The use of data Grids for sharing relevant data has proven to be successful in many research disciplines. However, the use of these environments when personal data are involved (such as in health) is reduced due to its lack of trust. There are many approaches that provide encrypted storages and key shares to prevent the access from unauthorized users. However, these approaches are additional layers that should be managed along with the authorization policies. We present in this paper a privacy-enhancing technique that uses encryption and relates to the structure of the data and their organizations, providing a natural way to propagate authorization and also a framework that fits with many use cases. The paper describes the architecture and processes, and also shows results obtained in a medical imaging platform.


     

A Precise Termination Condition of the Probabilistic Packet Marking Algorithm (2008)

ABSTRACT
The probabilistic packet marking (PPM) algorithm is a promising way to discover the Internet map or an attack graph that the attack packets traversed during a distributed denial-of-service attack. However, the PPM algorithm is not perfect, as its termination condition is not well defined in the literature. More importantly, without a proper termination condition, the attack graph constructed by the PPM algorithm would be wrong. In this work, we provide a precise termination condition for the PPM algorithm and name the new algorithm the Rectified PPM (RPPM) algorithm. The most significant merit of the RPPM algorithm is that when the algorithm terminates, the algorithm guarantees that the constructed attack graph is correct, with a specified level of confidence. We carry out simulations on the RPPM algorithm and show that the RPPM algorithm can guarantee the correctness of the constructed attack graph under 1) different probabilities that a router marks the attack packets and 2) different structures of the network graph. The RPPM algorithm provides an autonomous way for the original PPM algorithm to determine its termination, and it is a promising means of enhancing the reliability of the PPM algorithm.


     

Controlling IP Spoofing through Interdomain Packet Filters (2008)

ABSTRACT
The Distributed Denial-of-Service (DDoS) attack is a serious threat to the legitimate use of the Internet. Prevention mechanisms are thwarted by the ability of attackers to forge or spoof the source addresses in IP packets. By employing IP spoofing, attackers can evade detection and put a substantial burden on the destination network for policing attack packets. In this paper, we propose an inter-domain packet filter (IDPF) architecture that can mitigate the level of IP spoofing on the Internet. A key feature of our scheme is that it does not require global routing information. IDPFs are constructed from the information implicit in Border Gateway Protocol (BGP) route updates and are deployed in network border routers. We establish the conditions under which the IDPF framework correctly works in that it does not discard packets with valid source addresses. Based on extensive simulation studies, we show that, even with partial deployment on the Internet, IDPFs can proactively limit the spoofing capability of attackers. In addition, they can help localize the origin of an attack packet to a small number of candidate networks.


     

Modeling & Automated Containment of Worms (2008)

ABSTRACT
Self-propagating codes, called worms, such as Code Red, Nimda, and Slammer, have drawn significant attention due to their enormously adverse impact on the Internet. Thus, there is great interest in the research community in modeling the spread of worms and in providing adequate defense mechanisms against them. In this paper, we present a (stochastic) branching process model for characterizing the propagation of Internet worms. The model is developed for uniform scanning worms and then extended to preference scanning worms. This model leads to the development of an automatic worm containment strategy that prevents the spread of a worm beyond its early stage. Specifically, for uniform scanning worms, we are able to determine whether the worm spread will eventually stop. We then extend our results to contain uniform scanning worms. Our automatic worm containment schemes effectively contain both uniform scanning worms and local preference scanning worms, and it is validated through simulations and real trace data to be non intrusive.


     

An Adaptive Programming Model for Fault-Tolerant Distributed Computing (2007)

ABSTRACT
The capability of dynamically adapting to distinct runtime conditions is an important issue when designing distributed systems where negotiated quality of service (QoS) cannot always be delivered between processes. Providing fault tolerance for such dynamic environments is a challenging task. Considering such a context, this paper proposes an adaptive programming model for fault-tolerant distributed computing, which provides upper-layer applications with process state information according to the current system synchrony (or QoS). The underlying system model is hybrid, composed by a synchronous part (where there are time bounds on processing speed and message delay) and an asynchronous part (where there is no time bound). However, such a composition can vary over time, and, in particular, the system may become totally asynchronous (e.g., when the underlying system QoS degrade) or totally synchronous. Moreover, processes are not required to share the same view of the system synchrony at a given time. To illustrate what can be done in this programming model and how to use it, the consensus problem is taken as a benchmark problem. This paper also presents an implementation of the model that relies on a negotiated quality of service (QoS) for communication channels.


     

Provably Secure Three-Party Authenticated Quantum Key Distribution Protocols (2007)

ABSTRACT
The combination of 3AQKDP (implicit) and 3AQKDPMA (explicit) quantum cryptography is used to provide authenticated secure communication between sender and receiver. In quantum cryptography, quantum key distribution protocols (QKDPs) employ quantum mechanisms to distribute session keys and public discussions to check for eavesdroppers and verify the correctness of a session key. However, public discussions require additional communication rounds between a sender and receiver. The advantage of quantum cryptography easily resists replay and passive attacks. A 3AQKDP with implicit user authentication, which ensures that confidentiality, is only possible for legitimate users and mutual authentication is achieved only after secure communication using the session key start. In implicit quantum key distribution protocol (3AQKDP) have two phases such as setup phase and distribution phase to provide three party authentications with secure session key distribution. In this system there is no mutual understanding between sender and receiver. Both sender and receiver should communicate over trusted center. In explicit quantum key distribution protocol (3AQKDPMA) have two phases such as setup phase and distribution phase to provide three party authentications with secure session key distribution. I have mutual understanding between sender and receiver. Both sender and receiver should communicate directly with authentication of trusted center. Disadvantage of separate process 3AQKDP and 3AQKDPMA were providing the authentication only for message, to identify the security threads in the message. Not identify the security threads in the session key.


     

Packet Score A Statistics based packet filtering scheme against DDOS attack (2006)

ABSTRACT
Distributed Denial-of-Service attacks are a critical threat to the Internet. This paper introduces a distributed denial of service defense scheme that supports automated online attack characterizations and accurate attack packet discarding based on statistical processing. The key idea is to prioritize a packet based on a score which estimates its legitimacy given the attribute values it carries. Once the score of a packet is computed, this scheme performs score-based selective packet discarding where the dropping threshold is dynamically adjusted based on the score distribution of recent incoming packets and the current level of system overload. This paper describes the design and evaluation of automated attack characterizations, selective packet discarding, and an overload control process. Special considerations are made to ensure that the scheme is amenable to high-speed hardware implementation through scorebook generation and pipeline processing. A simulation study indicates that Packet Score is very effective in blocking several different attack types under many different conditions.


     

System-Wide Information Management (SWIM) Demonstration Security Architecture (2006)

ABSTRACT
System-Wide Information Management (SWIM) is a Federal Aviation Administration (FAA) network-centric environment that facilitates software application integration in the National Airspace System (NAS). Built on a set of five core service types Interfaces, Registries, Message Brokers, Information Assurance and System Management SWIM accelerates NAS evolution by defining a secure common infrastructure for application integration and a framework for information modeling and exchange. Providing information security in this distributed network centric environment is a significant challenge. System users must be confident that their critical data is protected. Competing requirements, the transportation of sensitive data and air-to-ground bandwidth constraints mean that a network layer based approach to security is no longer sufficient. Trusted security at every layer of a network-centric architecture - combined with strong identity management and a data-oriented approach to information assurance - is the key to success. This paper introduces the FAA SWIM demonstration security architecture, and explores some of the methods and mechanisms used to provide end-to end security, confidentiality, integrity, availability and privacy for NAS applications and their users.


     

A Novel Secure Communication Protocol  (2006)

ABSTRACT
An ad hoc network is a self organized entity with a number of mobile nodes without any centralized access point and also there is a topology control problem which leads to high power consumption and no security, while routing the packets between mobile hosts. Authentication is one of the important security requirements of a communication network. The common authentication schemes are not applicable in Ad hoc networks. In this paper, we propose a secure communication protocol for communication between two nodes in ad hoc networks. This is achieved by using clustering techniques. We present a novel secure communication framework for ad hoc networks (SCP); which describes authentication and confidentiality when packets are distributed between hosts with in the cluster and between the clusters. These cluster head nodes execute administrative functions and network key used for certification. The cluster head nodes (CHs) perform the major operations to achieve our SCP framework with help of Kerberos authentication application and symmetric key cryptography technique, which will be secure, reliable, transparent and scalable and will have less overhead.


     

DNS Security (2000)

ABSTRACT
The present article is an overview of the security problems affecting the Domain Name System and also of the solutions developed throughout the last years in order to provide a better, trustworthy and safer name resolution protocol for the expanding Internet community of present days. The paper discusses the basic notions regarding DNS and introduces the reader to the known security threats regarding DNS. The DNSSEC subset proposed is presented and analyzed from both theoretical and practical points of view, explaining the existing security features of the implementations available today.


     

Analysis on Credit Card Fraud Detection Methods 2011

ABSTRACT
Due to the rise and rapid growth of E-Commerce, use of credit cards for online purchases has dramatically increased and it caused an explosion in the credit card fraud. As credit card becomes the most popular mode of payment for both online as well as regular purchase, cases of fraud associated with it are also rising. In real life, fraudulent transactions are scattered with genuine transactions and simple pattern matching techniques are not often sufficient to detect those frauds accurately. Implementation of efficient fraud detection systems has thus become imperative for all credit card issuing banks to minimize their losses. Many modern techniques based on Artificial Intelligence, Data mining, Fuzzy logic, Machine learning, Sequence Alignment, Genetic Programming etc., has evolved in detecting various credit card fraudulent transactions. A clear understanding on all these approaches will certainly lead to an efficient credit card fraud detection system. This paper presents a survey of various techniques used in credit card fraud detection mechanisms and evaluates each methodology based on certain design criteria.
     

KTR: An Efficient Key Management Scheme for Secure Data Access Control in Wireless Broadcast Services 2010

ABSTRACT
Wireless broadcast is an effective approach for disseminating data to a number of users. To provide secure access to data in wireless broadcast services, symmetric-key-based encryption is used to ensure that only users who own the valid keys can decrypt the data. With regard to various subscriptions, an efficient key management for distributing and changing keys is in great demand for access control in broadcast services. In this paper, we propose an efficient key management scheme, namely, key tree reuse (KTR), to handle key distribution with regard to complex subscription options and user activities. KTR has the following advantages. First, it supports all subscription activities in wireless broadcast services. Second, in KTR, a user only needs to hold one set of keys for all subscribed programs instead of separate sets of keys for each program. Third, KTR identifies the minimum set of keys that must be changed to ensure broadcast security and minimize the rekey cost. Our simulations show that KTR can save about 45 percent of communication overhead in the broadcast channel and about 50 percent of decryption cost for each user compared with logical-key-hierarchy-based approaches.
     

Layered Approach Using Conditional Random Fields for Intrusion Detection 2010

ABSTRACT
Intrusion detection faces a number of challenges; an intrusion detection system must reliably detect malicious activities in a network and must perform efficiently to cope with the large amount of network traffic. In this project, we address these two issues of Accuracy and Efficiency using Conditional Random Fields and Layered Approach. We demonstrate that high attack detection accuracy can be achieved by using Conditional Random Fields and high efficiency by implementing the Layered Approach. Finally, we show that our system is robust and is able to handle noisy data without compromising performance.
     

A Puzzle-Based Defense Strategy against Flooding Attacks Using Game Theory 2010

ABSTRACT
In recent years, a number of puzzle-based defense mechanisms have been proposed against flooding denial-of-service (DoS) attacks in networks. Nonetheless, these mechanisms have not been designed through formal approaches and thereby some important design issues such as effectiveness and optimality have remained unresolved. This paper utilizes game theory to propose a series of optimal puzzle-based strategies for handling increasingly sophisticated flooding attack scenarios. In doing so, the solution concept of Nash equilibrium is used in a prescriptive way, where the defender takes his part in the solution as an optimum defense against rational attackers. This study culminates in a strategy for handling distributed attacks from an unknown number of sources.
     

SAT- Solving Approaches to Context-Aware Enterprise Network Security Management 2009

ABSTRACT
The project studies methodologies to automatically reach the configuration settings of an enterprise network that minimize security risks while taking into consideration the contextual requirements of an organization, such as accessibility of certain services. Enterprise network security management is a complex task of balancing security and usability, with trade-offs often necessary between the two. Past work has provided ways to identify intricate attack paths due to mis-configuration and vulnerabilities in an enterprise system, but little has been done to address how to correct the security problems within the context of various other requirements such as usability, ease of access, and cost of countermeasures. This paper presents an approach based on Boolean Satisfiability Solving (SAT Solving) that can reason about attacks, usability requirements, cost of actions, etc. in a unified, logical framework. Preliminary results show that the approach is both effective and efficient.
     

SYBILGUARD NETWORK 2008

ABSTRACT
Peer-to-peer and other decentralized, distributed systems are known to be particularly vulnerable to sybil attacks. In a sybil attack, a malicious user obtains multiple fake identities and pretends to be multiple, distinct nodes in the system. By controlling a large fraction of the nodes in the system, the malicious user is able to "out vote" the honest users in collaborative tasks such as Byzantine failure defenses. This paper presents SybilGuard, a novel protocol for limiting the corruptive influences of sybil attacks. Our protocol is based on the "social network" among user identities, where an edge between two identities indicates a human-established trust relationship. Malicious users can create many identities but few trust relationships.
     

Advanced Routing Technology for Fast Internet Protocol Network Recovery (2011)

ABSTRACT
As the Internet takes an increasingly central role in our communications infrastructure, the slow convergence o routing protocols after a network failure becomes a growing problem. To assure RAPID recovery from link and node failures in IP networks, we present a new recovery scheme called numerous Routing Configurations (NRC). Our proposed scheme guarantees recovery in all single failure scenarios, using a single mechanism to handle both link and node failures, and without knowing the root cause of the failure. NRC is strictly connectionless, and assumes only destination based hop-by-hop forwarding. NRC is based on keeping additional routing information in the routers, and allows packet forwarding to continue on an alternative output link immediately after the detection of a failure. It can be implemented with only minor changes to existing solutions. In this paper we presenters, and analyze its performance with respect to scalability, endorsement path lengths, and load distribution after a failure. We also show how an estimate of the traffic demands in the network can be used to improve the distribution of the recovered traffic, and thus reduce the chances of congestion when NRC is used.
     

Providing Rate Guarantees for Internet Application Traffic across ATM Networks  (2011)

ABSTRACT
The Transmission Control Protocol/Internet Protocol (TCP/IP) protocol suite is the standard requirement for all applications that need to communicate over the Internet. As TCP/IP applications are unable to specify the QoS parameters needed for most of the Asynchronous Transfer Mode (ATM) services, they tend to use the Unspecified Bit Rate (UBR) service category when running across ATM networks. The UBR service utilises any bandwidth which is left unused by the rest of the ATM services. This has led the ATM Forum’s Traffic Management group to define a new service category called Guaranteed Frame Rate (GFR). GFR is intended to provide minimum cell rate guarantees and fair access to excess bandwidth, left over from higher priority services. This article gives first a tutorial overview of GFR and then presents a survey of the research work which has been carried out towards the design and implementation of associated ATM switch mechanisms.
     

An Efficient Self-Organized Authentication and Key Management Scheme for Distributed Multihop Relay- Based IEEE 802.16 Networks (2011)

ABSTRACT
Wireless internet services are rapidly expanding and improving, it is important to provide users with not only high speed and high quality wireless service but also secured. Multihop relay-based support was added, which not only help for improving coverage and throughput but also provides features such as lower backhaul deployment cost, easy setup, robustness and re-configurability, which make it one of the indispensable technologies in next generation wireless network. A WiMAX network usually operates in a highly dynamic and open environment therefore it is known to be more vulnerable to security holes. Security holes most of the time is trade off with authentication and key management overheads. In order to operate securely, communication must be scheduled either by a distributed, centralized or hybrid security control algorithms with less authentication and key management overheads. In this paper, we propose a new fully self-organized efficient authentication and key management scheme (SEAKS) for hopby- hop distributed and localized security control for Multihop non-transparent relay based IEEE 802.16 networks which not only helps in security counter measures but also reduce the authentication and key maintenance overheads. The proposed scheme provides hybrid security controls between distributed authentication and localized re-authentication and key maintenance. The proposed scheme uses distributed nontransparent decode and forward relays for distributed authentication when any non-transparent Relays (NRS) want to join the networks and uses localized authentication when NRSs want to re-authenticate and do key maintenance. We analyze the procedures of the proposed scheme in details and examine how it works significantly to reduce overall authentication overheads and counter measures for security vulnerabilities such as Denial of Service, Replay and interleaving attacks.

     

A Permutation-Based Algorithm to Optimally Reschedule Trains in A Railway Traffic Network  (2011)

ABSTRACT
In this paper we discuss dynamic traffic management of railway traffic networks at an operational level. We design a model predictive controller based on measurements of the actual train positions. The core of the model predictive control approach is the railway traffic model, for which a switching max-plus linear system is proposed. If the model is affine in the controls, the optimization problem can be recast as a mixed-integer linear programming problem. To this end we present a permutation-based algorithm to model the rescheduling of trains running on the same track. We apply the algorithm to a simple railway traffic network simulation model and show a significant reduction of delays compared to the uncontrolled case.
     

Voronoi-based continuous query processing for mobile users  (2011)

ABSTRACT
Wireless data broadcast is a promising technique for information dissemination that leverages the computational capabilities of the mobile devices in order to enhance the scalability of the system. Under this environment, the data are continuously broadcast by the server, interleaved with some indexing information for query processing. Clients may then tune in the broadcast channel and process their queries locally without contacting the server. Previous work on spatial query processing for wireless broadcast systems has only considered snapshot queries over static data. In this paper, we propose an air indexing framework that 1) Outperforms the existing (i.e., snapshot) techniques in terms of energy consumption while achieving low access latency and 2) Constitutes the first method supporting efficient processing of continuous spatial queries over moving objects.
     

Multicast Multi-path Power Efficient Routing in Mobile ADHOC networks (2010)

ABSTRACT
This proposal of this project presents a measurement-based routing algorithm to load balance intra domain traffic along multiple paths for multiple multicast sources. Multiple paths are established using application-layer overlaying. The proposed algorithm is able to converge under different network models, where each model reflects a different set of assumptions about the multicasting capabilities of the network. The algorithm is derived from simultaneous perturbation stochastic approximation and relies only on noisy estimates from measurements. Simulation results are presented to demonstrate the additional benefits obtained by incrementally increasing the multicasting capabilities. The main application of mobile ad hoc network is in emergency rescue operations and battlefields. This project addresses the problem of power awareness routing to increase lifetime of overall network. Since nodes in mobile ad hoc network can move randomly, the topology may change arbitrarily and frequently at unpredictable times. Transmission and reception parameters may also impact the topology. Therefore it is very difficult to find and maintain an optimal power aware route
     

On Modeling, Analysis, and Optimization of Packet Aggregation Systems (2010)

ABSTRACT
In packet communication systems, a header is attached to the transmitted packet at each layer. The overhead due to the transmission of the individual header can have a significant impact on the performance of the communication system especially when the system operates in heavy load. In order to increase data throughput, a number of packets sharing a single header can be aggregated into a frame. In this paper, we present a mathematical model for a packet aggregation system assuming a general distribution for the packet length. For a given header size, we obtain the minimum system utilization where packet aggregation improves the system performance. We also analyze the asymptotic behavior of such systems leading to a simple heuristic policy on the optimum aggregation level. It is shown that the impact of the variability of the packet length distribution on different system performance measures is rather insignificant when the system load is low or moderate.


     

Host-to-Host Congestion Control for TCP (2010)

ABSTRACT
The Transmission Control Protocol (TCP) carries most Internet traffic, so performance of the Internet depends to a great extent on how well TCP works. Performance characteristics of a particular version of TCP are defined by the congestion control algorithm it employs. This paper presents a survey of various congestion control proposals that preserve the original host-to-host idea of TCP-namely, that neither sender nor receiver relies on any explicit notification from the network. The proposed solutions focus on a variety of problems, starting with the basic problem of eliminating the phenomenon of congestion collapse, and also include the problems of effectively using the available network resources in different types of environments (wired, wireless, high-speed, long-delay, etc.). In a shared, highly distributed, and heterogeneous environment such as the Internet, effective network use depends not only on how well a single TCP-based application can utilize the network capacity, but also on how well it cooperates with other applications transmitting data through the same network. Our survey shows that over the last 20 years many host-to-host techniques have been developed that address several problems with different levels of reliability and precision. There have been enhancements allowing senders to detect fast packet losses and route changes. Other techniques have the ability to estimate the loss rate, the bottleneck buffer size, and level of congestion. The survey describes each congestion control alternative, its strengths and its weaknesses. Additionally, techniques that are in common use or available for testing are described


     

Distributed Explicit Rate Schemes in Multi-Input–Multi-Output Network Systems (2010)

ABSTRACT
With the ever-increasing wireless/wired data applications recently, considerable efforts have focused on the design of distributed explicit rate flow control schemes for multi-input-multi-output service. This paper describes two novel wireless/wired multipoint-to-multipoint multicast flow control schemes, which are based on the distributed self-tuning proportional integrative plus derivative (SPID) controller and distributed self-tuning proportional plus integrative (SPI) controller, respectively. The control parameters can be designed to ensure the stability of the control loop in terms of source rate. The distributed explicit rate SPID and SPI controllers are located at the wireless/wired multipoint-to-multipoint multicast source to regulate the transmission rate. We further analyze the theoretical aspects of the proposed algorithm, and show how the control mechanism can be used to design a controller to support wireless/wired multipoint-to-multipoint multicast transmissions. Simulation results demonstrate the efficiency of the proposed scheme in terms of system stability, fast response, low packet loss, and high scalability, and the results also show SPID scheme has better performance than SPI scheme, however, SPID scheme requires more computing time and CPU resource


     

A Distributed Csma Algorithm For Throughput And Utility Maximization In Wireless Networks (2010)

ABSTRACT
In multihop wireless networks, designing distributed Scheduling algorithms to achieve the maximal throughput is a challenging problem because of the complex interference constraints among different links. Traditional maximal-weight scheduling (MWS), although throughput-optimal, is difficult to implement in distributed networks. On the other hand, a distributed greedy protocol similar to IEEE 802.11 does not guarantee the maximal throughput. In this paper, we introduce an adaptive carrier sense multiple access (CSMA) scheduling algorithm that can achieve the maximal throughput distributively. Some of the major advantages of the algorithm are that it applies to a very general interference model and that it is simple, distributed, and asynchronous. Furthermore, the algorithm is combined with congestion control to achieve the optimal utility and fairness of competing flows. Simulations verify the effectiveness of the algorithm. Also, the adaptive CSMA scheduling is a modular MAC-layer algorithm that can be combined with various protocols in the transport layer and network layer. Finally, the paper explores some implementation issues in the setting of 802.11 networks


     

Conditional Shortest Path Routing in Delay Tolerant Networks (2010)

ABSTRACT
Delay tolerant networks (DTNs) where each node knows the probabilistic distribution of contacts with other nodes. Delay tolerant networks are characterized by the sporadic connectivity between their nodes and therefore the lack of stable end-to-end paths from source to destination. Since the future node connections are mostly unknown in these networks, opportunistic forwarding is used to deliver messages. Based on the observations about human mobility traces and the findings of work, new metric called conditional intermeeting time is introduced. Based on the observations about human mobility traces and the findings of work, proposed system contains a new metric called conditional intermeeting time which computes the average intermeeting time between two nodes relative to a meeting with a third node using only the local knowledge of the past contacts. Compare CSPR protocol with the existing shortest path (SP) based routing protocol through real trace-driven simulations. The result demonstrates that CSPR achieves higher delivery rate and lower end-to-end delay compared to the shortest path based routing protocols.


     

On Wireless Scheduling Algorithms for Minimizing the Queue OverFlow Probability (2009)

ABSTRACT
In this paper, we are interested in wireless scheduling algorithms for the downlink of a single cell that can minimize the queue-over?ow probability. Speci?cally, in a large-deviation set- ting, we are interested in algorithms that maximize the asymptotic decay rate of the queue-over?ow probability, as the queue-over-?ow threshold approaches in?nity. We ?rst derive an upper bound on the decay rate of the queue-over?ow probability over all scheduling policies. We then focus on a class of scheduling algorithms collectively referred to as the "algorithms." For a given, the -algorithm picks the user for service at each time that has the largest product of the transmission rate multiplied by the backlog raised to the power. We show that when the over?ow metric is appropriately modi?ed, the minimum-cost-to-over?ow under the -algorithm can be achieved by a simple linear path, and it can be written as the solution of a vector-optimization problem. Using this structural property, we then show that when approaches in?nity, the -algorithms asymptotically achieve the largest decay rate of the queue-over?ow probability. Finally, this result enables us to design scheduling algorithms that are both close to optimal in terms of the asymptotic decay rate of the over?ow probability and empirically shown to maintain small queue-over?ow probabilities over queue-length ranges of practical interest


     

Study on Parallel Clustering Based on Asynchronous Communication (2009)

ABSTRACT
In order to improve the speed of clustering data mining, aiming at the characteristics of BIRCH algorithm, this paper has done research and analysis on rapid clustering data mining in the cluster system, and presented several improvement suggestions such as using data parallel thinking, uniform data distribution strategy , clustering communication mode and the optimization of clustering results. Experiment results show that the paralleling algorithm using asynchronous communication can achieve better performance and speedup than that synchronous one.


     

A New Reliable Broadcasting in Mobile Ad Hoc Networks (2009)

ABSTRACT
A New Reliable Broadcasting Algorithm for mobile ad-hoc networks will guarantee to deliver the messages from different sources to all the nodes of the network. The nodes are mobile and can move from one place to another. The solution does not require the nodes to know the network size, its diameter and number of nodes in the network. The only information a node has its identity (IP Address) and its position. On average, only a subset of nodes transmits and they transmit only once to achieve reliable broadcasting. The algorithm will calculate the relative position of the nodes with respect to the broadcasting source node. The nodes that are farthest from the source node will rebroadcast and this will minimize the number of rebroadcasts made by the intermediate nodes and will reduce the delay latency. The proposed algorithm will adapt itself dynamically to the number of concurrent broadcasts and will give the least finish time for any particular broadcast. It will be contention free, energy efficient and collision free.


     

Efficient Key Agreement for Large and Dynamic Multicast Groups (2009)

ABSTRACT
The Efficient key Agreement for Large and Dynamic Multicast Groups is used as the core component of many web and multimedia applications such as pay-TV, teleconferencing, real-time distribution of stock market price and etc. The main challenges for secure multicast are scalability, efficiency and authenticity. In this project, we propose a scalable, efficient, authenticated group key agreement scheme for large and dynamic multicast systems. The proposed key agreement scheme is identity-based which uses the bilinear map over the elliptic curves. Compared with the existing system, the proposed system provides group member authenticity without imposing extra mechanism. Furthermore, we give a scalability solution based on the subgroups, which has advantages over the existing schemes. Security analysis shows that our scheme satisfies both forward secrecy and backward secrecy.


     

Capturing Router Congestion and Delay (2009)

ABSTRACT
Using a unique monitoring experiment, we capture all packets crossing a (lightly utilized) operational access router from a Tier-1 provider, and use them to provide a detailed examination of router congestion and packet delays. The complete capture enables not just statistics as seen from outside the router, but also an accurate physical router model to be identified. This enables a comprehensive examination of congestion and delay from three points of view: the understanding of origins, measurement, and reporting. Our study defines new methodologies and metrics. In particular, the traffic reporting enables a rich description of the diversity of micro congestion behavior, without model assumptions, and at achievable computational cost.


     

Heuristic algorithms for designing self-repairing protection tress in mesh network (2009)

ABSTRACT
Protection trees have been used in the past for restoring multicast and Uni-cast traffic in networks in various failure scenarios. In this paper we focus on shared self-repairing trees for link protection in Uni-cast mesh networks. Shared protection trees have been proposed as a relatively simple approach that is easy to reconfigure and could provide sub-second restoration times with sub-optimal redundancy requirement. The self-repairing nature of this class of protection trees may make them an attractive option for cases where dynamic changes in network topology or demand may occur. In this paper, we present heuristic algorithms to design a self-repairing protection tree for a given network. We study the restorability performance of shared trees and examine the limitations of such schemes in specific topologies, such as cases where long node chains exist. Using extensive simulations with thousands of randomly generated network graphs. We compare redundancy and average backup path length of shared protection trees with optimal tree designs and non tree designs. We also apply our algorithms to the problem of designing the protection tree in a pre-designed fixed-capacity network, and study the performance of shared protection trees in this scenario under different network loads and link utilization levels.


     

Multiple Routing Configurations for Fast IP Network Recovery (2009)

ABSTRACT
As the Internet takes an increasingly central role in our communications infrastructure, the slow convergence of routing protocols after a network failure becomes a growing problem. To assure fast recovery from link and node failures in IP networks, we present a new recovery scheme called Multiple Routing Configurations (MRC). It can be implemented with only minor changes to existing solutions. In this paper we present MRC, and analyze its performance with respect to scalability, backup path lengths, and load distribution after a failure. We also show how an estimate of the traffic demands in the network can be used to improve the distribution of the recovered traffic, and thus reduce the chances of congestion when MRC is used.


     

Residual-Based Estimation of Peer and Link Lifetimes in P2P Networks (2009)

ABSTRACT
Existing methods of measuring lifetimes in P2P systems usually rely on the so-called Create-Based Method (CBM), which divides a given observation window into two halves and samples users created in the first half every time units until they die or the observation period ends. Despite its frequent use, this approach has no rigorous accuracy or overhead analysis in the literature. To shed more light on its performance, we first derive a model for CBM and show that small window size or large may lead to highly inaccurate lifetime distributions. We then show that create based sampling exhibits an inherent tradeoff between overhead and accuracy, which does not allow any fundamental improvement to the method. Instead, we propose a completely different approach for sampling user dynamics that keeps track of only residual lifetimes of peers and uses a simple renewal-process model to recover the actual lifetimes from the observed residuals. Our analysis indicates that for reasonably large systems, the proposed method can reduce bandwidth consumption by several orders of magnitude compared to prior approaches while simultaneously achieving higher accuracy. We finish the Project by implementing a two-tier Gnutella network crawler equipped with the proposed sampling method and obtain the distribution of ultra peer lifetimes in a network of 6.4 million users and 60 million links.


     

SIMPS Using Sociology for Personal Mobility (2009)

ABSTRACT
Assessing mobility in a thorough fashion is a crucial step toward more efficient mobile network design. Recent research on mobility has focused on two main points: analyzing models and studying their impact on data transport. These works investigate the consequences of mobility. This model defines a process called sociostation, rendered by two complimentary behaviors, namely socialize and isolate, that regulate an individual with regard to her/his own sociability level. SIMPS leads to results that agree with scaling laws observed both in small-scale and large-scale human motion. Although our model defines only two simple individual behaviors, we observe many emerging collective behaviors (group formation/splitting, path formation, and evolution).


     

Incremental Learning of Chunk Data for Online Pattern Classification Systems (2008)

ABSTRACT
This paper presents a pattern classification system in which feature extraction and classifier learning are simultaneously carried out not only online but also in one pass where training samples are presented only once. For this purpose, we have extended incremental principal component analysis (IPCA) and some classifier models were effectively combined with it. However, there was a drawback in this approach that training samples must be learned one by one due to the limitation of IPCA. To overcome this problem, we propose another extension of IPCA called chunk IPCA in which a chunk of training samples is processed at a time. In the experiments, we evaluate the classification performance for several large-scale data sets to discuss the scalability of chunk IPCA under one-pass incremental learning environments. The experimental results suggest that chunk IPCA can reduce the training time effectively as compared with IPCA unless the number of input attributes is too large. We study the influence of the size of initial training data and the size of given chunk data on classification accuracy and learning time. We also show that chunk IPCA can obtain major eigenvectors with fairly good approximation


     

A Bidirectional Routing Abstraction for Asymmetric Mobile Ad Hoc Networks (2008)

ABSTRACT
Wireless links are often asymmetric due to heterogeneity in the transmission power of devices, non-uniform environmental noise, and other signal propagation phenomenons. Unfortunately, routing protocols for mobile ad hoc networks typically work well only in bidirectional networks. This paper first presents a simulation study quantifying the impact of asymmetric links on network connectivity and routing performance. It then presents a framework called BRA that provides a bidirectional abstraction of the asymmetric network to routing protocols. BRA works by maintaining multi-hop reverse routes for unidirectional links and provides three new abilities: improved connectivity by taking advantage of the unidirectional links, reverse route forwarding of control packets to enable off-the-shelf routing protocols, and detection packet loss on unidirectional links. Extensive simulations of AODV layered on BRA show that packet delivery increases substantially (two-fold in some instances) in asymmetric networks compared to regular AODV, which only routes on bidirectional links.

     

A Geometric Approach to Improving Active Packet Loss Measurement (2008)

ABSTRACT
Measurement and estimation of packet loss characteristics are challenging due to the relatively rare occurrence and typically short duration of packet loss episodes. While active probe tools are commonly used to measure packet loss on end-to-end paths, there has been little analysis of the accuracy of these tools or their impact on the network. The objective of our study is to understand how to measure packet loss episodes accurately with end-to-end probes. We begin by testing the capability of standard Poisson- modulated end-to-end measurements of loss in a controlled laboratory environment using IP routers and commodity end hosts. Our tests show that loss characteristics reported from such Poisson-modulated probe tools can be quite inaccurate over a range of traffic conditions. Motivated by these observations, we introduce a new algorithm for packet loss measurement that is designed to overcome the deficiencies in standard Poisson-based tools. Specifically, our method entails probe experiments that follow a geometric distribution to 1) enable an explicit trade-off between accuracy and impact on the network, and 2) enable more accurate measurements than standard Poisson probing at the same rate. We evaluate the capabilities of our methodology experimentally by developing and implementing a prototype tool, called BADABING. The experiments demonstrate the trade-offs between impact on the network and measurement accuracy. We show that BADABING reports loss characteristics far more accurately than traditional loss measurement tools.


     

A Model-Based Approach to Evaluation of the Efficacy of FEC Coding In Combating Network Packet Losses (2008)

ABSTRACT
We propose a model-based analytic approach for evaluating the overall efficacy of FEC coding combined with interleaving in combating packet losses in IP networks. The loss of various packets during the data transmission can be reduced by using FEC coding. In this project we are going to evaluate the efficacy of FEC coding. Particularly modeling the network path in terms of a single bottleneck node. We develop a procedure for the exact evaluation of the packet-loss statistics for general arrival processes, based on a framework. We study both single-session and multiple-session scenarios, and provide a simple procedure for the more complicated multiple-session scenario. We show that the unified approach provides an integrated framework for exploring the tradeoffs between the key coding parameters; specifically, interleaving depths, channel coding rates and block lengths. The approach facilitates the selection of optimal coding strategies for different applications with various user quality-of-service (QoS) requirements and system constraints. We also provide an information-theoretic bound on the performance achievable with FEC coding in IP networks.


     

Cryptographic versus trust-based method for MANET routing security (2008)

ABSTRACT
Mobile Ad-hoc Networks (MANETs) allow wireless nodes to form a network without requiring a ?xed infrastructure. Early routing protocols for MANETs failed to take security issues into account. Subsequent proposals used strong cryptographic methods to secure the routing information. In the process, however, these protocols created new avenues for denial of service (DoS). Consequently, the trade-o? between security strength and DoS vulnerability has emerged as an area requiring further investigation. It is believed that di?erent trust methods can be used to develop protocols at various levels in this trade-o?. To gain a handle on this exchange, real world testing that evaluates the cost of existing proposals is necessary. Without this, future protocol design is mere speculation. In this paper, we give the first comparison of SAODV and TAODV, two MANET routing protocols, which address routing security through cryptographic and trust-based means respectively. We provide performance comparisons on actual resource-limited hardware. Finally, we discuss design decisions for future routing protocols


     

Designing Less-Structured P2P Systems for the Expected High Churn (2008)

ABSTRACT
We address the problem of highly transient populations in unstructured and loosely structured peer-to-peer (P2P) systems. We propose a number of illustrative query-related strategies and organizational protocols that, by taking into consideration the expected session times of peers (their lifespan), yield systems with performance characteristics more resilient to the natural instability of their environments. We first demonstrate the benefits of lifespan-based organizational protocols in terms of end-application performance and in the context of dynamic and heterogeneous Internet environments. We do this using a number of currently adopted and proposed query-related strategies, including methods for query distribution, caching, and replication. We then show, through trace-driven simulation and wide-area experimentation, the performance advantages of lifespan-based, query-related strategies when layered over currently employed and lifespan-based organizational protocols. While merely illustrative, the evaluated strategies and protocols clearly demonstrate the advantages of considering peers session time in designing widely-deployed P2P systems.


     

Dual-Link Failure Resiliency through Backup Link Mutual Exclusion (2008)

ABSTRACT
Networks employ link protection to achieve fast recovery from link failures. While the first link failure can be protected using link protection, there are several alternatives for protecting against the second failure. This paper formally classifies the approaches to dual-link failure resiliency. One of the strategies to recover from dual-link failures is to employ link protection for the two failed links independently, which requires that two links may not use each other in their backup paths if they may fail simultaneously. Such a requirement is referred to as backup link mutual exclusion (BLME) constraint and the problem of identifying a backup path for every link that satisfies the above requirement is referred to as the BLME problem. This paper develops the necessary theory to establish the sufficient conditions for existence of a solution to the BLME problem. Solution methodologies for the BLME problem is developed using two approaches by: 1) formulating the backup path selection as an integer linear program; 2) developing a polynomial time heuristic based on minimum cost path routing. The ILP formulation and heuristic are applied to six networks and their performance is compared with approaches that assume precise knowledge of dual-link failure. It is observed that a solution exists for all of the six networks considered. The heuristic approach is shown to obtain feasible solutions that are resilient to most dual-link failures, although the backup path lengths may be significantly higher than optimal. In addition, the paper illustrates the significance of the knowledge of failure location by illustrating that network with higher connectivity may require lesser capacity than one with a lower connectivity to recover from dual-link failures


     

Minimizing File Download Time in Stochastic Peer-to-Peer Networks (2008)

ABSTRACT
The peer to peer(p2p) file-sharing application are becoming increasingly popular and account for more than 70% of the Internets bandwidth usage. Measurement studies show several hour s depending on the level of network congestion or the capacity fluctuation. We consider two major factors that have significant impact on average download time, namely spatial service capability in different source peer.


     

On Performance Benefits of Multihoming Route Control (2008)

ABSTRACT
Multi homing is increasingly being employed by large enterprises and data centers to extract good performance and reliability from their ISP connections. Multi homed end networks today can employ a variety of route control products to optimize their Internet access performance and reliability. However, little is known about the tangible benefits that such products can offer the mechanisms they employ and their trade-offs. This paper makes two important contributions. First, we present a study of the potential improvements in Internet round-trip times (RTTs) and transfer speeds from employing multi homing route control. Our analysis shows that multi homing to three or more ISPs and cleverly scheduling traffic across the ISPs can improve Internet RTTs and throughputs by up to 25% and 20%, respectively. However, a careful selection of ISPs is important to realize the performance improvements. Second, focusing on large enterprises, we propose and evaluate a wide-range of route control mechanisms and evaluate their design trade-offs. We implement the proposed schemes on a Linux-based Web proxy and perform a trace-based evaluation of their performance. We show that both passive and active measurement-based techniques are equally effective and could improve the Web response times of enterprise networks by up to 25% on average, compared to using a single ISP. We also outline several best common practices for the design of route control products.


     

Performance of a Speculative Transmission Scheme for Scheduling-Latency Reduction (2008)

ABSTRACT
This work was motivated by the need to achieve low latency in an input-queued centrally-scheduled cell switch for high-performance computing applications; specifically, the aim is to reduce the latency incurred between a request and response arrival of the corresponding grant. The minimum latency in switches with centralized scheduling comprises two components, namely, the control-path latency and the data-path latency, which in a practical high-capacity, distributed switch implementation can be far greater than the cell duration. We introduce a speculative transmission scheme to significantly reduce the average control-path latency by allowing cells to proceed without waiting for a grant, under certain conditions. It operates in conjunction with any centralized matching algorithm to achieve a high maximum utilization. Using this model, performance measures such as the mean delay and the rate of successful speculative transmissions are derived. The results demonstrate that the latency can be almost entirely eliminated between request and response for loads up to 50%. Our simulations confirm the analytical results.


     

Rate & Delay Guarantees Provided By Close Packet Switches with Load Balancing (2008)

ABSTRACT
The size of a single-hop cross-bar fabric is still limited by the technology, and the fabrics available on the market do not exceed the terabit capacity. A multi hop fabric such as Clos network provides the higher capacity by using the smaller switching elements (SE). When the traffic load is balanced over the switches in a middle stage, all the traffic would get through the fabric, as long as the switch outputs are not overloaded. However, the delay that packets experience through the Clos switch depends on the granularity of flows that are balanced. We examine the maximum fabric utilization under which a tolerable delay is provided for various load balancing algorithms, and derive the general formula for this utilization in terms of the number of flows that are balanced. We show that the algorithms which balance flows with sufficiently coarse granularity provide both high fabric utilization and delay guarantees to the most sensitive applications. Since no admission control should be performed within the switch, the fast traffic-pattern changes can be accommodated in the proposed scalable architecture.


     

A New TCP for Persistent Packet Reordering (2006)

ABSTRACT
Most standard implementations of TCP perform poorly when packets are reordered. In this paper, we propose a new version of TCP that maintains high throughput when reordering occurs and yet, when packet reordering does not occur, is friendly to other versions of TCP. The proposed TCP variant, or TCP-PR, does not rely on duplicate acknowledgments to detect a packet loss. Instead, timers are maintained to keep track of how long ago a packet was transmitted. In case the corresponding acknowledgment has not yet arrived and the elapsed time since the packet was sent is larger than a given threshold, the packet is assumed lost. Because TCP-PR does not rely on duplicate acknowledgments, packet reordering (including out-or-order acknowledgments) has no effect on TCP-PRs performance. Through extensive simulations, we show that TCP-PR performs consistently better than existing mechanisms that try to make TCP more robust to packet reordering. In the case that packets are not reordered, we verify that TCP-PR maintains the same throughput as typical implementations of TCP (specifically, TCP SACK) and shares network resources fairly. Furthermore, TCP-PR only requires changes to the TCP sender side making it easier to deploy.


     

Distributed Collaborative Key Agreement and Authentication Protocols for Dynamic Peer Groups (2006)

ABSTRACT
We consider several distributed collaborative key agreement and authentication protocols for dynamic peer groups. There are several important characteristics which make this problem different from traditional secure group communication. They are: • Distributed nature in which there is no centralized key server; • Collaborative nature in which the group key is contributory (i.e., each group member will collaboratively contribute its part to the global group key); • Dynamic nature in which existing members may leave the group while new members may join.


     

Implementing Multicast Distribution Through Recursive Unicast Trees (2006)

ABSTRACT
IP multicast is facing a slow take-off although it has been a hotly debated topic for more than a decade. Many reasons are responsible for this status. Hence, the Internet is likely to be organized with both uni-cast and multicast enabled networks. Thus, it is of utmost importance to design protocols that allow the progressive deployment of the multicast service by supporting uni-cast clouds. This paper presents HBH (hop-by-hop hybrid routing protocol). HBH adopts the source-specific channel abstraction to simplify address allocation and implements data distribution using recursive uni-cast trees, which allow the transparent support of uni-cast- only routers. An important original feature of HBH is its tree construction algorithm that takes into account the uni-cast routing asymmetries. Since most multicast routing protocols rely on the uni-cast infrastructure, the uni-cast asymmetries impact the structure of the multicast trees. We show through simulation that HBH outperforms other multicast routing protocols in terms of the delay experienced by the receivers and the bandwidth consumption of the multicast trees. Additionally, we show that HBH can be incrementally deployed and that with a small fraction of HBH-enabled routers in the network HBH outperforms application-layer multicast.


     

Energy-Efficient SINR-Based Routing for Multihop Wireless Networks  (2006)

ABSTRACT
In this paper, we develop an energy-efficient routing scheme that takes into account the interference created by existing flows in the network. The routing scheme chooses a route such that the network expends the minimum energy satisfying with the minimum constraints of flows. Unlike previous works, we explicitly study the impact of routing a new flow on the energy consumption of the network. Using implementation. We show that the routes chosen by our algorithm (centralized and distributed) are more energy efficient than the state of the art.


     

A Distributed Database Architecture for Global Roaming in Next-Generation Mobile Networks (2004)

ABSTRACT
The next-generation mobile network will support terminal mobility, personal mobility, and service provider portability, making global roaming seamless. A location-independent personal telecommunication number (PTN) scheme is conducive to implementing such a global mobile system. However, the non-geographic PTNs coupled with the anticipated large number of mobile users in future mobile networks may introduce very large centralized databases. This necessitates research into the design and performance of high-throughput database technologies used in mobile systems to ensure that future systems will be able to carry efficiently the anticipated loads. This paper proposes scalable, robust, efficient location database architecture based on the location- independent PTNs. The proposed multi-tree database architecture consists of a number of database subsystems, each of which is a three-level tree structure and is connected to the others only through its root. By exploiting the localized nature of calling and mobility patterns, the proposed architecture effectively reduces the database loads as well as the signaling traffic incurred by the location registration and call delivery procedures. In addition, two memory-resident database indices, memory-resident direct file and T-tree are proposed for the location databases to further improve their throughput. Analysis model and numerical results are presented to evaluate the efficiency of the proposed database architecture. Results have revealed that the proposed database architecture for location management can effectively support the anticipated high user density in the future mobile networks.


     

An Algorithmic approach to identify network link failures  (2004)

ABSTRACT
Due to the Internets sheer size, complexity, and various routing policies, it is difficult if not impossible to locate the causes of large volumes of BGP update messages that occur from time to time. To provide dependable global data delivery we need diagnostic tools that can pinpoint the exact Connectivity changes. In this paper we describe an algorithm, called MVS Change that can pin down the origin of routing changes due to any single link failure or link restoration. Using a simplified model of BGP, called Simple Path Vector Protocol (SPVP), and a graph model of the Internet, MVS Change takes as input the SPVP update messages collected from multiple vantage points and accurately locates the link that initiated the routing changes. We provide theoretical proof for the correctness of the design.


     

Efficient, Authenticated, Fault-Tolerant Key Agreement for Dynamic Peer Group  (2004)

ABSTRACT
We present an efficient authenticated and fault-tolerant protocol (AFTD) for tree-based key agreement. Our approach is driven by the insight that when a Diffie-Hellman blinded key is updated, in a tree-based method, it suffices to send the update to a small subset of the group, instead of entire group, as current methods require. Our scheme distributes each updated public key to a relatively small subgroup, called its trust set, greatly improving performance. Moreover, we use a threshold secret sharing method to distribute the function of the trusted authority across trust sets, thereby guaranteeing key authentication, enhancing fault-tolerance, and protecting our protocol from impersonation attacks. Our performance analysis suggests that our scheme significantly reduces the communication overhead and storage requirement.


     

Network Border Patrol Preventing Congestion Collapse (2004)

ABSTRACT
The end-to-end nature of Internet congestion control is an important factor in its scalability and robustness. However, end-to-end congestion control algorithms alone are incapable of preventing the congestion collapse and unfair bandwidth allocations created by applications that are unresponsive to network congestion. To address this flaw, we propose and investigate a novel congestion avoidance mechanism called Network Border Patrol (NBP). NBP relies on the exchange of feedback between routers at the borders of a network in order to detect and restrict unresponsive traffic flows before they enter the network. An enhanced core-stateless fair queuing mechanism is proposed in order to provide fair bandwidth allocations among competing flows. NBP is compliant with the Internet philosophy of pushing complexity toward the edges of the network whenever possible. Simulation results show that NBP effectively eliminates congestion collapse that, when combined with fair queuing, NBP achieves approximately max-min fair bandwidth allocations for competing network flows.


     

ITP: An Image Transport Protocol for the Internet  (2004)

ABSTRACT
Images account for a significant and growing fraction of Web downloads. The traditional approach to transporting images uses TCP, which provides a generic reliable in-order byte stream abstraction, but which is overly restrictive for image data. We analyze the progression of image quality at the receiver with time, and show that the in-order delivery abstraction provided by a TCP-based approach prevents the receiver application from processing and rendering portions of an image when they actually arrive. The end result is that an image is rendered in bursts interspersed with long idle times rather than smoothly.


     

CACHING STRATEGIES BASED ON INFORMATION DENSITY ESTIMATION IN WIRELESS AD HOC NETWORKS 2011

ABSTRACT
Cooperative caching in wireless networks, where the nodes may be mobile and exchange information in a peer-to-peer fashion. We consider both cases of nodes with largeand small-sized caches. For large-sized caches, we devise a strategy where nodes, independent of each other, decide whether to cache some content and for how long. In the case of small sized caches, we aim to design a content replacement strategy that allows nodes to successfully store newly received information while maintaining the good performance of the content distribution system. Under both conditions, each node takes decisions according to its perception of what nearby users may store in their caches and with the aim of differentiating its own cache content from the other nodes’. The result is the creation of content diversity within the nodes neighborhood so that a requesting user likely finds the desired information nearby. We simulate our caching algorithms in different ad hoc network scenarios and compare them with other caching schemes, showing that our solution succeeds in creating the desired content diversity, thus leading to a resource-efficient information access.
     

A Review of the Applications of Agent Technology In Traffic and Transportation Systems  2011

ABSTRACT
The agent computing paradigm is rapidly emerging as one of the powerful technologies for the development of large-scale distributed systems to deal with the uncertainty in a dynamic environment. The domain of traffic and transportation systems is well suited for an agent-based approach because transportation systems are usually geographically distributed in dynamic changing environments. Our literature survey shows that the techniques and methods resulting from the field of agent and multiagent systems have been applied to many aspects of traffic and transportation systems, including modeling and simulation, dynamic routing and congestion management, and intelligent traffic control. This paper examines an agent-based approach and its applications in different modes of transportation, including roadway, railway, and air transportation. This paper also addresses some critical issues in developing agent-based traffic control and management systems, such as interoperability, flexibility, and extendibility.
     

SCALABLE AND COST-EFFECTIVE INTERCONNECTION OF DATA-CENTER SERVERS USING DUAL SERVER PORTS 2011

ABSTRACT
The goal of data-center networking is to interconnect a large number of server machines with low equipment cost while providing high network capacity and high bisection width. It is well understood that the current practice where servers are connected by a tree hierarchy of network switches cannot meet these requirements. In this paper, we explore a new server-interconnection structure. We observe that the commodity server machines used in today’s data centers usually come with two built-in Ethernet ports, one for network connection and the other left for backup purposes. We believe that if both ports are actively used in network connections, we can build a scalable, cost-effective interconnection structure without either the expensive higher-level large switches or any additional hardware on servers. We have proven that FiConn is highly scalable to encompass hundreds of thousands of servers with low diameter and high bisection width. We have developed a low-overhead traffic-aware routing mechanism to improve effective link utilization based on dynamic traffic state. We have also proposed how to incrementally deploy FiConn.
     

A Unified Approach to Optimizing Performance in Networks Serving Heterogeneous Flows  2011

ABSTRACT
We study the optimal control of communication networks in the presence of heterogeneous traffic requirements. Specifically, we distinguish the flows into two crucial classes: inelastic for modeling high-priority, delay-sensitive, and fixed-throughput applications; and elastic for modeling low-priority, delay-tolerant, and throughput-greedy applications. We note that the coexistence of such diverse flows creates complex interactions at multiple levels (e.g., flow and packet levels), which prevent the use of earlier design approaches that dominantly assume homogeneous traffic. In this work, we develop the mathematical framework and novel design methodologies needed to support such heterogeneous requirements and propose provably optimal network algorithms that account for the multilevel interactions between the flows. To that end, we first formulate a network optimization problem that incorporates the above throughput and service prioritization requirements of the two traffic types. We, then develop a distributed joint load-balancing and congestion control algorithm that achieves the dual goal of maximizing the aggregate utility gained by the elastic flows while satisfying the fixed throughput and prioritization requirements of the inelastic flows. Next, we extend our joint algorithm in two ways to further improve its performance: in delay through a virtual queue implementation with minimal throughput degradation and in utilization by allowing for dynamic multi-path routing for elastic flows. A unique characteristic of our proposed dynamic routing solution is the novel two-stage queueing architecture it introduces to satisfy the service prioritization requirement.
     

Node Isolation Model and Age-Based Neighbor Selection in Unstructured P2P Networks 2009

ABSTRACT
Previous analytical studies of unstructured P2P resilience have assumed exponential user lifetimes and only considered age-independent neighbor replacement. In this paper, we overcome these limitations by introducing a general node-isolation model for heavy-tailed user lifetimes and arbitrary neighbor-selection algorithms. Using this model, we analyze two age-biased neighbor-selection strategies and show that they significantly improve the residual lifetimes of chosen users, which dramatically reduces the probability of user isolation and graph partitioning compared with uniform selection of neighbors. In fact, the second strategy based on random walks on age-proportional graphs demonstrates that, for lifetimes with infinite variance, the system monotonically increases its resilience as its age and size grow. Specifically, we show that the probability of isolation converges to zero as these two metrics tend to infinity.We finish the paper with simulations in finite-size graphs that demonstrate the effect of this result in practice.
     

TCP Performance in Flow-Based Mix Networks: Modeling and Analysis 2009

ABSTRACT
This System focuses on the theoretical analysis and simulation study of mix network TCP performance for flow-based anonymity applications. Anonymity has become a necessary and legitimate aim in many application areas, including anonymous Web browsing and file sharing. There are two requirements for a successful anonymous communication system: the degree of anonymity the system can achieve (anonymity degree) and the quality of service (QoS). Although a significant effort has been directed at discovering attacks against anonymity networks and developing countermeasures to those attacks, there is little systematic QoS analysis for such security and privacy systems. We model and analyze the performance of TCP in Flow based mix networks. Anonymity technologies such as mix networks have gained increasing attention as a way to provide communication privacy. Mix networks were developed for message-based applications such as e-mail, but researchers have adapted mix techniques to low-latency flow-based applications such as anonymous Web browsing. To improve TCP performance, we examined the approach of increasing TCP’s duplicate threshold parameter and derived formulas for the performance gains.
     

Designing Less-Structured P2P Systems For the Expected High Churn  2008

ABSTRACT
We address the problem of highly transient populations in unstructured and loosely structured peer-to-peer (P2P) systems. We propose a number of illustrative query-related strategies and organizational protocols that, by taking into consideration the expected session times of peers (their lifespan), yield systems with performance characteristics more resilient to the natural instability of their environments. We first demonstrate the benefits of lifespan-based organizational protocols in terms of end-application performance and in the context of dynamic and heterogeneous Internet environments. We do this using a number of currently adopted and proposed query-related strategies, including methods for query distribution, caching, and replication. We then show, through trace-driven simulation and wide-area experimentation, the performance advantages of lifespan-based, query-related strategies when layered over currently employed and lifespan-based organizational protocols. While merely illustrative, the evaluated strategies and protocols clearly demonstrate the advantages of considering peers’ session time in designing widely-deployed P2P systems
     

Enhancing Search Performance in Unstructured P2P Networks Based On User’s Common Intrest 2008

ABSTRACT
Peer-to-peer (P2P) networks establish loosely coupled application-level overlays on top of the Internet to facilitate efficient sharing of resources. They can be roughly classified as either structured or unstructured networks. Without stringent constraints over the network topology, unstructured P2P networks can be constructed very efficiently and are therefore considered suitable to the Internet environment. However, the random search strategies adopted by these networks usually perform poorly with a large network Size. In this paper, we seek to enhance the search performance in unstructured P2P networks through exploiting users’ common interest patterns captured within a probability-theoretic framework termed the user interest model (UIM). A search protocol and a routing table updating protocol are further proposed in order to expedite the search process through self organizing the P2P network into a small world. Both theoretical and experimental analyses are conducted and demonstrated the effectiveness and efficiency of our approach.
     

Clustering with Multi-Viewpoint based Similarity Measure (2011)

ABSTRACT
All clustering methods have to assume some cluster relationship among the data objects that they are applied on. Similarity between a pair of objects can be defined either explicitly or implicitly. In this paper, we introduce a novel multi-viewpoint based similarity measure and two related clustering methods. The major difference between a traditional dissimilarity/similarity measure and ours is that the former uses only a single viewpoint, which is the origin, while the latter utilizes many different viewpoints, which are objects assumed to not be in the same cluster with the two objects being measured. Using multiple viewpoints, more informative assessment of similarity could be achieved. Theoretical analysis and empirical study are conducted to support this claim. Two criterion functions for document clustering are proposed based on this new measure. We compare them with several well-known clustering algorithms that use other popular similarity measures on various document collections to verify the advantages of our proposal.


     

The CoQUOS Approach to Continuous Queries in Unstructured Overlays (2011)

ABSTRACT
The current peer-to-peer (P2P) content distribution systems are constricted by their simple on-demand content discovery mechanism. The utility of these systems can be greatly enhanced by incorporating two capabilities, namely a mechanism through which peers can register their long term interests with the network so that they can be continuously notified of new data items, and a means for the peers to advertise their contents. Although researchers have proposed a few unstructured overlay-based publish-subscribe systems that provide the above capabilities, most of these systems require intricate indexing and routing schemes, which not only make them highly complex but also render the overlay network less flexible toward transient peers. This paper argues that for many P2P applications, implementing full-fledged publish-subscribe systems is an overkill. For these applications, we study the alternate continuous query paradigm, which is a best-effort service providing the above two capabilities. We present a scalable and effective middleware, called CoQUOS, for supporting continuous queries in unstructured overlay networks. Besides being independent of the overlay topology, CoQUOS preserves the simplicity and flexibility of the unstructured P2P network. Our design of the CoQUOS system is characterized by two novel techniques, namely cluster-resilient random walk algorithm for propagating the queries to various regions of the network and dynamic probability-based query registration scheme to ensure that the registrations are well distributed in the overlay. Further, we also develop effective and efficient schemes for providing resilience to the churn of the P2P network and for ensuring a fair distribution of the notification load among the peers. This paper studies the properties of our algorithms through theoretical analysis. We also report series of experiments evaluating the effectiveness and the costs of the proposed schemes.


     

Decision Trees for Uncertain Data (2011)

ABSTRACT
Traditional decision tree classifiers work with data whose values are known and precise. We extend such classifiers to handle data with uncertain information. Value uncertainty arises in many applications during the data collection process. Example sources of uncertainty include measurement/quantization errors, data staleness, and multiple repeated measurements. With uncertainty, the value of a data item is often represented not by one single value, but by multiple values forming a probability distribution. Rather than abstracting uncertain data by statistical derivatives (such as mean and median), we discover that the accuracy of a decision tree classifier can be much improved if the “complete information” of a data item (taking into account the probability density function (pdf)) is utilized.
We extend classical decision tree building algorithms to handle data tuples with uncertain values. Extensive experiments have been conducted that show that the resulting classifiers are more accurate than those using value averages. Since processing pdf’s is computationally more costly than processing single values (e.g., averages), decision tree construction on uncertain data is more CPU demanding than that for certain data. To tackle this problem, we propose a series of pruning techniques that can greatly improve construction efficiency.


     

Effective navigation of query results Based on concept hierarchies (2011)

ABSTRACT
Search queries on biomedical databases, such as PubMed, often return a large number of results, only a small subset of which is relevant to the user. Ranking and categorization, which can also be combined, have been proposed to alleviate this information overload problem. Results categorization for biomedical databases is the focus of this work. A natural way to organize biomedical citations is according to their MeSH annotations. MeSH is a comprehensive concept hierarchy used by PubMed. In this paper, we present the BioNav system, a novel search interface that enables the user to navigate large number of query results by organizing them using the MeSH concept hierarchy. First, the query results are organized into a navigation tree. At each node expansion step, BioNav reveals only a small subset of the concept nodes, selected such that the expected user navigation cost is minimized. In contrast, previous works expand the hierarchy in a predefined static manner, without navigation cost modeling. We show that the problem of selecting the best concepts to reveal at each node expansion is NP-complete and propose an efficient heuristic as well as a feasible optimal algorithm for relatively small trees. We show experimentally that BioNav outperforms state-of-the-art categorization systems with respect to the user navigation cost.


     

Temporal Data Clustering via Weighted Clustering Ensemble with Different Representations (2011)

ABSTRACT
Temporal data clustering provides underpinning techniques for discovering the intrinsic structure and condensing information over temporal data. In this paper, we present a temporal data clustering framework via a weighted clustering ensemble of multiple partitions produced by initial clustering analysis on different temporal data representations. In our approach, we propose a novel weighted consensus function guided by clustering validation criteria to reconcile initial partitions to candidate consensus partitions from different perspectives, and then, introduce an agreement function to further reconcile those candidate consensus partitions to a final partition. As a result, the proposed weighted clustering ensemble algorithm provides an effective enabling technique for the joint use of different representations, which cuts the information loss in a single representation and exploits various information sources underlying temporal data. In addition, our approach tends to capture the intrinsic structure of a data set, e.g., the number of clusters. Our approach has been evaluated with benchmark time series, motion trajectory, and time-series data stream clustering tasks. Simulation results demonstrate that our approach yields favorite results for a variety of temporal data clustering tasks. As our weighted cluster ensemble algorithm can combine any input partitions to generate a clustering ensemble, we also investigate its limitation by formal analysis and empirical studies.


     

A New Method for Generating All Positive and Negative Association Rules (2011)

ABSTRACT
Association Rule play very important role in recent scenario of data mining. But we have only generated positive rule, negative rule also useful in today data mining task. In this paper we are proposing "A new method for generating all positive and negative Association Rules" (NRGA).NRGA generates all association rules which are hidden when we have applied Apriori Algorithm. For representation of Negative Rules we are giving new name of this rules as like: CNR, ANR, and ACNR. In this paper we are also modify Correlation coefficient (CRC) equation, so all generate results are very promising. First we apply Apriori Algorithm for frequent itemset generation and that is also generate positive rules, after on frequent itemset we apply NRGA algorithm for all negative rules generation and optimize generated rules using Genetic Algorithm

     

An Efficient Density Based Improved K- Medoids Clustering Algorithm (2011)

ABSTRACT
Clustering is the process of classifying objects into different groups by partitioning sets of data into a series of subsets called clusters. Clustering has taken its roots from algorithms like k-medoids and k-medoids. However conventional k-medoids clustering algorithm suffers from many limitations. Firstly, it needs to have prior knowledge about the number of cluster parameter k. Secondly, it also initially needs to make random selection of k representative objects and if these initial k medoids are not selected properly then natural cluster may not be obtained. Thirdly, it is also sensitive to the order of input dataset. Mining knowledge from large amounts of spatial data is known as spatial data mining. It becomes a highly demanding field because huge amounts of spatial data have been collected in various applications ranging from geo-spatial data to bio-medical knowledge. The database can be clustered in many ways depending on the clustering algorithm employed, parameter settings used, and other factors. Multiple clustering can be combined so that the final partitioning of data provides better clustering. In this paper, an efficient density based k-medoids clustering algorithm has been proposed to overcome the drawbacks of DBSCAN and kmedoids clustering algorithms. The result will be an improved version of kmedoids clustering algorithm. This algorithm will perform better than DBSCAN while handling clusters of circularly distributed data points and slightly overlapped clusters

     

Improving Utilization of Infrastructure Clouds (2011)

ABSTRACT
A key advantage of Infrastructure-as-a-Service (IaaS) clouds is providing users on-demand access to resources. However, to provide on-demand access, cloud providers must either significantly overprovision their infrastructure (and pay a high price for operating resources with low utilization) or reject a large proportion of user requests (in which case the access is no longer on-demand). At the same time, not all users require truly on-demand access to resources. Many applications and workflows are designed for recoverable systems where interruptions in service are expected. For instance, many scientists utilize High Throughput Computing (HTC)-enabled resources, such as Condor, where jobs are dispatched to available resources and terminated when the resource is no longer available.We propose a cloud infrastructure that combines on-demand allocation of resources with opportunistic provisioning of cycles from idle cloud nodes to other processes by deploying backfill Virtual Machines (VMs). For demonstration and experimental evaluation, we extend the Nimbus cloud computing toolkit to deploy backfill VMs on idle cloud nodes for processing an HTC workload. Initial tests show an increase in IaaS cloud utilization from 37.5% to 100% during a portion of the evaluation trace but only 6.39% overhead cost for processing the HTC workload. We demonstrate that a shared infrastructure between IaaS cloud providers and an HTC job management system can be highly beneficial to both the IaaS cloud provider and HTC users by increasing the utilization of the cloud infrastructure (thereby decreasing the overall cost) and contributing cycles that would otherwise be idle to processing HTC jobs

     

Glip: A Concurrency Control Protocol For Clipping Indexing (2011)

ABSTRACT
The project Concurrency Control Protocol for Clipping Indexing deals with the multidimensional databases. In multidimensional indexing trees, the overlapping of nodes will tend to degrade query performance, as one single point query may need to traverse multiple branches of the tree if the query point is in an overlapped area. Multidimensional databases are beginning to be used in a wide range of applications. To meet this fast-growing demand, the R-tree family is being applied to support fast access to multidimensional data, for which the R+-tree exhibits outstanding search performance. In order to support efficient concurrent access in multiuser environments, concurrency control mechanisms for multidimensional indexing have been proposed. However, these mechanisms cannot be directly applied to the R+-tree because an object in the R+-tree may be indexed in multiple leaves. This paper proposes a concurrency control protocol for R-tree variants with object clipping, namely, Granular Locking for clipping indexing (GLIP). GLIP is the first concurrency control approach specifically designed for the R+-tree and its variants, and it supports efficient concurrent operations with serializable isolation, consistency, and deadlock-free. Experimental tests on both real and synthetic data sets validated the effectiveness and efficiency of the proposed concurrent access framework

     

Closeness: A New Privacy Measure For Data Publishing 2010

ABSTRACT
The k-anonymity privacy requirement for publishing micro data requires that each equivalence class (i.e., a set of records that are indistinguishable from each other with respect to certain "identifying" attributes) contains at least k records. Recently, several authors have recognized that k-anonymity cannot prevent attribute disclosure. The notion of `-diversity has been proposed to address this; `-diversity requires that each equivalence class has at least ` well-represented values for each sensitive attribute. In this article, we show that `-diversity has a number of limitations. In particular, it is neither necessary nor sufficient to prevent attribute disclosure. Motivated by these limitations, we propose a new notion of privacy called "closeness". We first present the base model t- closeness, which requires that the distribution of a sensitive attribute in any equivalence class is close to the distribution of the attribute in the overall table (i.e., the distance between the two distributions should be no more than a threshold t). We then propose a more flexible privacy model called (n, t)-closeness that offers higher utility. We describe our desiderata for designing a distance measure between two probability distributions and present two distance measures. We discuss the rationale for using closeness as a privacy measure and illustrate its advantages through examples and experiments.


     

Record Matching over Query Results from Multiple Web Databases (2010)

ABSTRACT
Record matching, which identifies the records that represent the same real-world entity, is an important step for data integration. Most state-of-the-art record matching methods are supervised, which requires the user to provide training data. These methods are not applicable for the Web database scenario, where the records to match are query results dynamically generated on the- fly. Such records are query-dependent and a prelearned method using training examples from previous query results may fail on the results of a new query. To address the problem of record matching in the Web database scenario, we present an unsupervised, online record matching method, UDD, which, for a given query, can effectively identify duplicates from the query result records of multiple Web databases. After removal of the same-source duplicates, the "presumed" nonduplicate records from the same source can be used as training examples alleviating the burden of users having to manually label training examples. Starting from the nonduplicate set, we use two cooperating classifiers, a weighted component similarity summing classifier and an SVM classifier, to iteratively identify duplicates in the query results from multiple Web databases. Experimental results show that UDD works well for the Web database scenario where existing supervised methods do not apply.


     

Study on Intelligent E-Shopping System Based on Data Mining (2009)

ABSTRACT
E-commerce is a related concept of data mining technologies and the realization process of data mining techniques are described. Combine data mining and guide features of e-shopping site, study intelligent shopping guide system based on data mining. Use data mining technology to guide customers to buy goods or to provide recommendations in order to provide higher quality services. We take the specific case as study object, we use data mining techniques to analyze and propose solutions. The use of data mining provide users with intelligent guide and make users easy in the range of goods which not only save user browsing net and considering time, but also provide users with a good proposal to allow the user to get the appropriate selection of goods, is a kind of high-quality services.


     

Discriminative Learning and Recognition of Image Set Classes Using Canonical Correlations  (2009)

ABSTRACT
We address the problem of comparing sets of images for object recognition, where the sets may represent variations in an objects appearance due to changing camera pose and lighting conditions. Canonical Correlations (also known as principal or canonical angles), which can be thought of as the angles between two d-dimensional subspaces, have recently attracted attention for image set matching. Canonical correlations offer many benefits in accuracy, efficiency, and robustness compared to the two main classical methods: parametric distribution-based and nonparametric sample-based matching of sets. Here, this is first demonstrated experimentally for reasonably sized data sets using existing methods exploiting canonical correlations. Motivated by their proven effectiveness, a novel discriminative learning method over sets is proposed for set classification. Specifically, inspired by classical Linear Discriminate Analysis (LDA), we develop a linear discriminate function that maximizes the canonical correlations of within-class sets and minimizes the canonical correlations of between-class sets. Image sets transformed by the discriminate function are then compared by the canonical correlations. Classical orthogonal subspace method (OSM) is also investigated for the similar purpose and compared with the proposed method. The proposed method is evaluated on various object recognition problems using face image sets with arbitrary motion captured under different illuminations and image sets of 500 general objects taken at different views. The method is also applied to object category recognition using ETH-80 database. The proposed method is shown to outperform the state-of-the-art methods in terms of accuracy and efficiency.


     

Mining Medical Databases with Modified Gini Index Classification (2008)

ABSTRACT
Decision tree classification is a common method used in data mining. It has been used for predicting medical diagnoses. Among data mining methods for classification, decision trees have several advantages such as they are simple to understand and interpret; they are able to handle both numerical and categorical attributes. However, it is well-known that when Gini index is used for classification, the method biases multivalued attributes. In addition to having difficulty when the number of classes is large, the method also tends to favor tests that result in equalsized partitions and purity in all partitions. In this paper, we modify the Gini-based decision tree method. To overcome the known problems, we normalize the Gini indexes by taking into account information about the splitting status of all attributes. Instead of using the Gini index for attribute selection as usual, we use ratios of Gini indexes and their splitting values in order to reduce the biases. We report our experiments with several benchmark medical data bases


     

Distributed Frequent Itemset Mining using Trie Data Structure (2008)

ABSTRACT
Finding association rules is one of the most investigated fields of data mining. Computation and communication are two important factors in distributed association rule mining. In this problem Association rules are generated by first mining of frequent itemsets in distributed data. In this paper we proposed a new distributed trie-based algorithm (DTFIM) to find frequent itemsets. This algorithm is proposed for a multi-computer environment. In second phase we added an idea from FDM algorithm for candidate generation step. Experimental evaluations on different sort of distributed data show the effect of using this algorithm and adopted techniques


     

Fuzzy Concept Mining Based On Formal Concept Analysis (2008)

ABSTRACT
Data Mining (also known as Knowledge Discovery) is defined as the non-trivial extraction of implicit, previously unknown, and potentially useful information from data. It includes not only methods for extracting information from the given data, but also visualizing the information. Formal Concept Analysis (FCA) is one of Data mining research fields, and it has been applied to a number of areas such as medicine, psychology, library, information science, and software re-engineering and others


     

Efficient Approximate Query Processing in Peer-to-Peer Networks (2007)

ABSTRACT
Peer-to-peer (P2P) databases are becoming prevalent on the Internet for distribution and sharing of documents, applications, and other digital media. The problem of answering large-scale ad hoc analysis queries, for example, aggregation queries, on these databases poses unique challenges. Exact solutions can be time consuming and difficult to implement, given the distributed and dynamic nature of P2P databases. In this paper, we present novel sampling-based techniques for approximate answering of ad hoc aggregation queries in such databases. Computing a high-quality random sample of the database efficiently in the P2P environment is complicated due to several factors: the data is distributed (usually in uneven quantities) across many peers, within each peer, the data is often highly correlated, and, moreover, even collecting a random sample of the peers is difficult to accomplish. To counter these problems, we have developed an adaptive two-phase sampling approach based on random walks of the P2P graph, as well as block-level sampling techniques. We present extensive experimental evaluations to demonstrate the feasibility of our proposed solution.


     

On Natural Language Processing and Plan Recognition (2007)

ABSTRACT
Natural language processing (NLP) is a subfield of artificial intelligence and linguistics. It studies the problems of automated generation and understanding of natural human languages. Natural language generation systems convert information from computer databases into normal-sounding human language, and natural language understanding systems convert samples of human language into more formal representations that are easier for computer programs to manipulate. Natural Language Processing is the artificial intelligent concept where the machines understand Natural Languages like English, Korean, French, Telugu, Hindi.. etc., We are going to develop a tool that will take the Database queries in the form natural language and then processes it and gives the result. This includes many sub components like Language Analyzer, Query Builder and Viewer. The system will first parses the query in natural language and finds the major parts in the string. Then first it will look for the table name and then it parses the string for the where clause and then for the order by clause. After parsing it will construct the query string based on the data available. The generated SQL query is posted to the database to fetch the results.


     

A Near-Optimal Multicast Scheme For Mobile Ad Hoc Networks Using A Hybrid Genetic Algorithm  (2007)

ABSTRACT
An ad-hoc mobile network is a collection of mobile nodes that are dynamically and arbitrarily located in such a manner that the interconnections between nodes are capable of changing on a continual basis. The primary goal of such an ad-hoc network routing protocol is correct and efficient route establishment between a pair of nodes so that messages may be delivered in a timely manner. Multicasting is to send single copy of a packet to all of those of Partners that requested it, and not to send multiple copies of a packet over the same portion of the network, nor to send packets to Partners who dont want it.


     

A Secure Routing Protocol for mobile Ad-hoc Network (2006)

ABSTRACT
Most recent ad hoc network research has focused on providing routing services without considering security. In this paper, we detail security threats against ad hoc routing protocols, specifically examining AODV and DSR. In light of these threats, we identify three different environments with distinct security requirements. We propose a solution to one, the managed-open scenario where no network infrastructure is pre-deployed, but a small amount of prior security coordination is expected. Our protocol, ARAN, is based on certificates and successfully defeats all identified attacks.


     

Distributed Collaborative Key Agreement AND Authentication Protocols for Dynamic Peer Groups (2006)

ABSTRACT
We consider several distributed collaborative key agreement and authentication protocols for dynamic peer groups. There are several important characteristics which make this problem different from traditional secure group communication. They are: 1) distributed nature in which there is no centralized key server; 2) collaborative nature in which the group key is contributory (i.e., each group member will collaboratively contribute its part to the global group key); and 3) dynamic nature in which existing members may leave the group while new members may join. Instead of performing individual rekeying operations, i.e., re-computing the group key after every join or leave request, we discuss an interval-based approach of rekeying. We consider three interval-based distributed rekeying algorithms, or interval-based algorithms for short, for updating the group key: 1) The Rebuild algorithm; 2) The Batch algorithm; and 3) The Queue-batch algorithm. Performance of these three interval-based algorithms under different settings, such as different join and leave probabilities, is analyzed. We show that the interval-based algorithms significantly outperform the individual rekeying approach and that the Queue-batch algorithm performs the best among the three interval-based algorithms. More importantly, the Queue-batch algorithm can substantially reduce the computation and communication workload in a highly dynamic environment. We further enhance the interval-based algorithms in two aspects: authentication and implementation. Authentication focuses on the improvement, while implementation realizes the interval-based algorithms in real network settings. Our work provides a fundamental understanding about establishing a group key via a distributed and collaborative approach for a dynamic peer group.


     

A Signature-Based Indexing Method for Efficient Content-Based Retrieval of Relative Temporal Patterns (2008)

ABSTRACT
A number of algorithms have been proposed for the discovery of datas from the large database. However, since the number of generated patterns can be large, selecting which patterns to analyze can be nontrivial. There is thus a need for algorithms and tools that can assist in the selection of discovered patterns so that subsequent analysis can be performed in an efficient and, ideally, interactive manner. In this project, we propose a signature-based indexing method to optimize the storage and retrieval of a relative datas from the large database.


     

An Efficient Clustering Scheme to Exploit Hierarchical Data in Network Traffic Analysis (2008)

ABSTRACT
There is significant interest in the data mining and network management communities about the need to improve existing techniques for clustering multivariate network traffic flow records so that we can quickly infer underlying traffic patterns. In this paper, we investigate the use of clustering techniques to identify interesting traffic patterns from network traffic data in an efficient manner. We develop a framework to deal with mixed type attributes including numerical, categorical, and hierarchical attributes for a one-pass hierarchical clustering algorithm. We demonstrate the improved accuracy and efficiency of our approach in comparison to previous work on clustering network traffic.


     

C-TREND Temporal Cluster Graphs for Identifying and Visualizing Trends in Multi attribute Transactional Data (2008)

ABSTRACT
Organizations and firms are capturing increasingly more data about their customers, suppliers, competitors, and business environment. Most of this data is multi-attribute (multidimensional) and temporal in nature. Data mining and business intelligence techniques are often used to discover patterns in such data; however, mining temporal relationships typically is a complex task. This paper proposes a new data analysis and visualization technique for representing trends in multi-attribute temporal data using a clustering based approach. This paper introduce Cluster-based Temporal Representation of Event Data (C-TREND), a system that implements the temporal cluster graph construct, which maps multi-attribute temporal data to a two-dimensional directed graph that identifies trends in dominant data types over time. This paper present temporal clustering-based technique, discuss its algorithmic implementation and performance, demonstrate applications of the technique by analyzing data on wireless networking technologies and baseball batting statistics, and introduce a set of metrics for further analysis of discovered trends.


     

Online Index Recommendations for High-Dimensional Databases Using Query Workloads (2008)

ABSTRACT
High-dimensional databases pose a challenge with respect to efficient access. High-dimensional indexes do not work because of the often-cited "curse of dimensionality. However, users are usually interested in querying data over a relatively small subset of the entire attribute set at a time. A potential solution is to use lower dimensional indexes that accurately represent the user access patterns. A query response using the physical database design that is developed based on a static snapshot of the query workload may significantly degrade if the query patterns change. To address these issues, we introduce a parameterizable technique to recommend indexes based on index types that are frequently used for high-dimensional data sets and to dynamically adjust indexes as the underlying query workload changes. We incorporate a query pattern change detection mechanism to determine when the access patterns have changed enough to warrant change in the physical database design. By adjusting analysis parameters, We trade off analysis speed against analysis resolution. We perform experiments with a number of data sets, query sets, and parameters to show the effect that varying these characteristics has on analysis results.


     

Protection of Database Security via Collaborative Inference Detection (2008)

ABSTRACT
Malicious users can exploit the correlation among data to infer sensitive information from a series of seemingly innocuous data accesses. Thus, we develop an inference violation detection system to protect sensitive data content based on data dependency, database schema and semantic knowledge. We constructed a semantic inference model (SIM) that represents the possible inference channels from any attribute to the pre-assigned sensitive attributes. The SIM is then instantiated to a semantic inference graph (SIG) for query-time inference violation detection. For a single user case, when a user poses a query, the detection system will examine his/her past query log and calculate the probability of inferring sensitive information. The query request will be denied if the inference probability exceeds the pre specified threshold. For multi-user cases, the users may share their query answers to increase the inference probability. Therefore, we develop a model to evaluate collaborative inference based on the query sequences of collaborators and their task-sensitive collaboration levels. Experimental studies reveal that information authoritativeness, communication fidelity and honesty in collaboration are three key factors that affect the level of achievable collaboration. An example is given to illustrate the use of the proposed technique to prevent multiple collaborative users from deriving sensitive information via inference.


     

Truth Discovery with Multiple Conflicting Information Providers on the We (2008)

ABSTRACT
The world-wide web has become the most important information source for most of us. Unfortunately, there is no guarantee for the correctness of information on the web. Moreover, different web sites often provide conflicting in-formation on a subject, such as different specifications for the same product. In this paper we propose a new problem called Veracity that is conformity to truth, which studies how to find true facts from a large amount of conflicting information on many subjects that is provided by various web sites. We design a general framework for the Veracity problem, and invent an algorithm called Truth Finder, which utilizes the relationships between web sites and their information, i.e., a web site is trustworthy if it provides many pieces of true information, and a piece of information is likely to be true if it is provided by many trustworthy web sites. Our experiments show that Truth Finder successfully finds true facts among conflicting information, and identifies trustworthy web sites better than the popular search engines.


     

Hiding Sensitive Association Rules with Limited Side Effects (2007)

ABSTRACT
Data mining techniques have been widely used in various applications. However, the misuse of these techniques may lead to the disclosure of sensitive information. Researchers have recently made efforts at hiding sensitive association rules. Nevertheless, undesired side effects, e.g., non-sensitive rules falsely hidden and spurious rules falsely generated may be produced in the rule hiding process. In this paper, we present a novel approach that strategically modifies a few transactions in the transaction database to decrease the supports or confidences of sensitive rules without producing the side effects. Since the correlation among rules can make it impossible to achieve this goal, in this paper, we propose heuristic methods for increasing the number of hidden sensitive rules and reducing the number of modified entries. The experimental results show the effectiveness of our approach, i.e., undesired side effects are avoided in the rule hiding process. The results also report that in most cases, all the sensitive rules are hidden without spurious rules falsely generated. Moreover, the good scalability of our approach in terms of database size and the influence of the correlation among rules on rule hiding are observed.


     

Energy Efficient Routing in Wireless Ad Hoc Networks (2005)

ABSTRACT
Ad hoc wireless networks are power constrained since nodes operate with limited battery energy. Thus, energy consumption is crucial in the design of new ad hoc routing protocols. To design such protocols, we have to look away from the traditional minimum hop routing schemes. In this paper, we propose three extensions to the state-of-the-art shortest-cost routing algorithm, AODV. The discovery mechanism in these extensions (LEAR-AODV, PAR-AODV, and LPR-AODV) uses energy consumption as a routing metric. They reduce the energy consumption of the nodes by routing packets to their destination using energy-optimal routes. We show that these algorithms improve the network survivability by maintaining the network connectivity. They carry out this objective with low overhead and without affecting the other wireless network protocol layers.


     

GHIC A Hierarchical Pattern-Based Clustering Algorithm for Grouping Web Transactions (2005)

ABSTRACT
Grouping customer transactions into segments may help understand customers better. The marketing literature has concentrated on identifying important segmentation variables (e.g., customer loyalty) and on using cluster analysis and mixture models for segmentation. The data mining literature has provided various clustering algorithms for segmentation without focusing specifically on clustering customer transactions. Building on the notion that observable customer transactions are generated by latent behavioral traits, in this paper, we investigate using a pattern-based clustering approach to grouping customer transactions. We define an objective function that we maximize in order to achieve a good clustering of customer transactions and present an algorithm, GHIC that groups customer transactions such that item sets generated from each cluster, while similar to each other, are different from ones generated from others. We present experimental results from user-centric Web usage data that demonstrates that GHIC generates a highly effective clustering of transactions.


     

Ranking Spatial Data by Quality Preferences 2011

ABSTRACT
A spatial preference query ranks objects based on the qualities of features in their spatial neighborhood. For example, using a real estate agency database of flats for lease, a customer may want to rank the flats with respect to the appropriateness of their location, defined after aggregating the qualities of other features (e.g., restaurants, cafes, hospital, market, etc.) within their spatial neighborhood. Such a neighborhood concept can be specified by the user via different functions. It can be an explicit circular region within a given distance from the flat. Another intuitive definition is to assign higher weights to the features based on their proximity to the flat. In this paper, we formally define spatial preference queries and propose appropriate indexing techniques and search algorithms for them. Extensive evaluation of our methods on both real and synthetic data reveals that an optimized branch-and-bound solution is efficient and robust with respect to different parameters.
     

Deriving Concept-Based User Profiles from Search Engine Logs 2010

ABSTRACT
User profiling is a fundamental component of any personalization applications. Most existing user profiling strategies are based on objects that users are interested in (i.e., positive preferences), but not the objects that users dislike (i.e., negative preferences). In this paper, we focus on search engine personalization and develop several concept-based user profiling methods that are based on both positive and negative preferences. We evaluate the proposed methods against our previously proposed personalized query clustering method. Experimental results show that profiles which capture and utilize both of the user’s positive and negative preferences perform the best. An important result from the experiments is that profiles with negative preferences can increase the separation between similar and dissimilar queries. The separation provides a clear threshold for an agglomerative clustering algorithm to terminate and improve the overall quality of the resulting query clusters.
     

Data Mining for Secure Software Engineering-Source Code Management Tool Case Study 2010

ABSTRACT
Data Mining for Software Engineering: To improve software productivity and quality, software engineers are increasingly applying data mining algorithms to various software engineering tasks. However mining software engineering data poses several challenges, requiring various algorithms to effectively mine sequences, graphs and text from such data. Software engineering data includes code bases, execution traces, historical code changes, mailing lists and bug data bases. They contains a wealth of information about a projects-status, progress and evolution. Using well established data mining techniques, practitioners and researchers can explore the potential of this valuable data in order to better manage their projects and do produce higher-quality software systems that are delivered on time and with in budget. Data mining can be used in gathering and extracting latent security requirements, extracting algorithms and business rules from code, mining legacy applications for requirements and business rules for new projects etc.
     

Staying Connected in a Mobile Healthcare System: Experiences from the MediNet Project  2010

ABSTRACT
A mobile healthcare system consists of a number of components networked together including patients and their healthcare providers. It is important in this type of system for the patient to remain connected at all times even if one of the communication components fails. This paper discusses the design of the MediNet system and shows how it seamlessly handles connectivity issues between patients and their mobile phones, between the healthcare meters and mobile phones, and between mobile phones and web server components. The overall goal behind our design strategies is to continue providing a high level of service to the patient in the face of communication problems leading to improved acceptability and trust of the system by patients.
     

ANGEL: Enhancing the Utility of Generalization For Privacy Preserving Publication  2009

ABSTRACT
Generalization is a well-known method for privacy preserving data publication. Despite its vast popularity, it has several drawbacks such as heavy information loss, difficulty of supporting marginal publication, and so on. To overcome these drawbacks, we develop ANGEL, a new anonymization technique that is as effective as generalization in privacy protection, but is able to retain significantly more information in the micro data. ANGEL is applicable to any monotonic principles (e.g., l-diversity, t-closeness, etc.), with its superiority (in correlation preservation) especially obvious when tight privacy control must be enforced. We show that ANGEL lends itself elegantly to the hard problem of marginal publication. In particular, unlike generalization that can release only restricted marginals, our technique can be easily used to publish any marginals with strong privacy guarantees.
     

EFFICIENT CLUSTERING TECHNIQUES FOR MANAGING LARGE DATASETS 2009

ABSTRACT
Cluster analysis is a more primitive technique in that no assumptions are made concerning the number of groups or the group structure. Groupings are done on the basis of similarities or distances (dissimilarities). The inputs required are similarity measures or data from which similarities can be computed. Cluster analysis of a tool for exploring the structure of data. The core of cluster analysis is clustering. The process of grouping objects into clusters such that the objects from the same cluster are similar and objects from different clusters are dissimilar. Objects can be described in terms of measurements (example, attributes, features) or by relationships with other objects (example, pair wise distance, similarity). Unlike classification, clustering does not require assumptions about category labels that tag objects with prior identifiers. Therefore, clustering is an unsupervised learning technique versus classification, which belongs to supervised learning. The need to structure and learn from the vigorously growing amounts of data has been a driving force for making clustering a highly active research area. Humans are not able to easily discover knowledge from the glut of information in databases without the use of summarization techniques. Basic statistics (such as mean, variance) or histograms can provide an initial feel for the data. However, more intricate relationships among the objects, among the features, and between both can be discovered through cluster analysis.
     

ABSTRACT

     

EXACT KNOWLEDGE HIDING THROUGH DATABASE EXTENSION 2009

ABSTRACT
The objective of this project is to provide an optimal solution for the hiding of sensitive frequent item sets using border-based approach. This approach applies an extension to the original database instead of either modifying existing transactions (directly or through the application of transformations) or rebuilding the data set to accommodate knowledge hiding. The extended portion of the data set contains a set of carefully crafted transactions that achieve to lower the importance of the sensitive patterns to a degree that they become uninteresting from the perspective of the data mining algorithm, while minimally affecting the importance of the non sensitive ones. The hiding process is guided by the need to maximize the data utility of the sanitized database by introducing the least possible amount of side effects, such as 1) the hiding of non sensitive patterns or 2) the production of frequent patterns that were not existent in the initial data set (ghost item sets). The released database, which consists of the initial part (original database) and the extended part (database extension), can guarantee the protection of the sensitive knowledge, when mined at the same or higher support as the one used in the original database.
     

Histogram-Based Global Load Balancing in Structured Peer-to-Peer Systems 2009

ABSTRACT
Load balancing is a classical problem and a research hotspot of web intelligence. DNS load balancing is the pioneer load balancing technology. But the existing DNS dynamic load balancing strategies have shortages. This paper puts forward a new load balancing method, which is to connect extension theory with load balancing. Extension engineering method is initially proposed by Prof. CaiWen. It has been successfully used in various applications. In this paper, we use the operation of matter-element theory, extension set, and dependent function in extension theory as well as the membership degree of fuzzy math to set up an extension-based dynamic load balancing model of heterogeneous server cluster. It is proved by experiment that the load balancing strategy is more effective, dynamic, steadygoingand in real time by using this new model.
     

IMine: Index Support for Item Set Mining 2009

ABSTRACT
This paper presents the IMine index, a general and compact structure which provides tight integration of item set extraction in a relational DBMS. Since no constraint is enforced during the index creation phase, IMine provides a complete representation of the original database. To reduce the I/O cost, data accessed together during the same extraction phase are clustered on the same disk block. The IMine index structure can be efficiently exploited by different item set extraction algorithms. In particular, IMine data access methods currently support the FP-growth and LCM v.2 algorithms, but they can straightforwardly support the enforcement of various constraint categories.
     

Learning in an Ambient Intelligent World: Enabling Technologies and Practices 2009

ABSTRACT
The rapid evolution of information and communication technology opens a wide spectrum of opportunities to change our surroundings into an Ambient Intelligent (AmI) world. AmI is a vision of future information society, where people are surrounded by a digital environment that is sensitive to their needs, personalized to their requirements, anticipatory of their behavior, and responsive to their presence. It emphasizes on greater user friendliness, user empowerment, and more effective service support, with an aim to bring information and communication technology to everyone, every home, every business, and every school, thus improving the quality of human life. AmI unprecedentedly enhances learning experiences by endowing the users with the opportunities of learning in context, a breakthrough from the traditional education settings. In this survey paper, we examine some major characteristics of an AmI learning environment. To deliver a feasible and effective solution to ambient learning, we overview a few latest developed enabling technologies in context awareness and interactive learning. Associated practices are meanwhile reported. We also describe our experience in designing and implementing a smart class prototype, which allows teachers to simultaneously instruct both local and remote students in a context-aware and natural way.
     

Distributed Frequent Itemset Mining using Trie Data Structure  2008

ABSTRACT
In this project, I focus on Association Rule Mining (ARM) because of its immense popularity and usefulness in a wide varity situations such as electronic commerce, classification , clustering, Web mining, and bioinformatics. Several data structures have been proposed for the enhancement of ARM, but none is able to cope effectively with the size and dynamism of current databases. Here, I shall critically examine existing preprocessing data structures in association rule mining for enhancing performance in an attempt to understand their strengths and weaknesses. My analysis culminate in a practical structure called the Support-Ordered Trie Itemset (SOTrieIT) and two synergistic association rule mining algorithms to accompany it In this problem Association rules are generated by first mining of frequent itemsets in distributed data. In this project, I proposed a new distributed trie-based algorithm (DTFIM) to find frequent itemsets. This algorithm is proposed for a multi-computer environment. In second phase, I added an idea from FDM algorithm for candidate generation step. Experimental evaluations on different sort of distributed data show the effect of using this algorithm and adopted techniques. The problem of mining association rules is to discover all rules user-defined that have confidence and support greater than some thresholds. ARM can be decomposed into two subproblems: The discovery of frequent itemsets and the generation of association rules from frequent itemsets. Researchers usually address the first subproblem as it is more computationally expensive and less straightforward. As such, only the first subproblem is addressed here.
     

ODAM: An Optimized Distributed Association Rule Mining Algorithm 2004

ABSTRACT
With the explosive growth of information sources available on the World Wide Web, it has become increasingly necessary for users to utilize automated tools in find the desired information resources, and to track and analyze their usage patterns. Association rule mining is an active data mining research area. However, most ARM algorithms cater to a centralized environment. In contrast to previous ARM algorithms, ODAM is a distributed algorithm for geographically distributed data sets that reduces communication costs. Recently, as the need to mine patterns across distributed databases has grown, Distributed Association Rule Mining (D-ARM) algorithms have been developed. These algorithms, however, assume that the databases are either horizontally or vertically distributed. In the special case of databases populated from information extracted from textual data, existing D-ARM algorithms cannot discover rules based on higher-order associations between items in distributed textual documents that are neither vertically nor horizontally distributed, but rather a hybrid of the two. Modern organizations are geographically distributed. Typically, each site locally stores its ever increasing amount of day-to-day data. Using centralized data mining to discover useful patterns in such organizations' data isn't always feasible because merging data sets from different sites into a centralized site incurs huge network communication costs. Data from these organizations are not only distributed over various locations but also vertically fragmented, making it difficult if not impossible to combine them in a central location. Distributed data mining has thus emerged as an active subarea of data mining research. A significant area of data mining research is association rule mining. Unfortunately, most ARM algorithms focus on a sequential or centralized environment where no external communication is required. Distributed ARM algorithms, on the other hand, aim to generate rules from different data sets spread over various geographical sites; hence, they require external communications throughout the entire process. DARM algorithms must reduce communication costs so that generating global association rules costs less than combining the participating sites' data sets into a centralized site. However, most DARM algorithms don't have an efficient message optimization technique, so they exchange numerous messages during the mining process. We have developed a distributed algorithm, called Optimized Distributed Association Mining, for geographically distributed data sets. ODAM generates support counts of candidate itemsets quicker than other DARM algorithms and reduces the size of average transactions, data sets, and message exchanges.
     

DATA CLUSTERING USING PARTICLE SWARM OPTIMIZATION 2003

ABSTRACT
This paper proposes two new approaches to using PSO to cluster data. It is shown how PSO can he used to find the centroids of a user specified number of clusters. The algorithm is then extended to use K-means clustering to seed the initial swarm. This second alga. rithm basically uses PSO to refine the clusters formed by K-means. The new PSO algorithms are evaluated on six data sets, and compared to the performance of K-means clustering. Results show that both PSO clustering techniques have much potential.
     

Secure and Practical Outsourcing of Linear Programming in Cloud Computing  2011

ABSTRACT
Cloud Computing has great potential of providing robust computational power to the society at reduced cost. It enables customers with limited computational resources to outsource their large computation workloads to the cloud, and economically enjoy the massive computational power, bandwidth, storage, and even appropriate software that can be shared in a pay-per-use manner. Despite the tremendous benefits, security is the primary obstacle that prevents the wide adoption of this promising computing model, especially for customers when their confidential data are consumed and produced during the computation. On the one hand, the outsourced computation workloads often contain sensitive information, such as the business financial records, proprietary research data, or personally identifiable health information etc. To combat against unauthorized information leakage, sensitive data have to be encrypted before outsourcing so as to provide end to- end data confidentiality assurance in the cloud and beyond. However, ordinary data encryption techniques in essence prevent cloud from performing any meaningful operation of the underlying plaintext data, making the computation over encrypted data a very hard problem. On the other hand, the operational details inside the cloud are not transparent enough to customers. As a result, there do exist various motivations for cloud server to behave unfaithfully and to return incorrect results, i.e., they may behave beyond the classical semi honest model.
     

A study on certificate revocation in Mobile ad hoc networks  (2011)

ABSTRACT
Certificate revocation is an important security component in mobile ad hoc networks (MANETs). Owing to their wireless and dynamic nature, MANETs are vulnerable to security attacks from malicious nodes. Certificate revocation mechanisms play an important role in securing a network. When the certificate of a malicious node is revoked, it is denied from all activities and isolated from the network. The main challenge for certificate revocation is to revoke the certificates of malicious nodes promptly and accurately. In this paper, we build upon our previously proposed scheme, a clustering based certificate revocation scheme, which outperforms other techniques in terms of being able to quickly revoke attackers' certificates and recover falsely accused certificates. However, owing to a limitation in the schemes certificate accusation and recovery mechanism, the number of nodes capable of accusing malicious nodes decreases over time. This can eventually lead to the case where malicious nodes can no longer be revoked in a timely manner. To solve this problem, we propose a new method to enhance the effectiveness and efficiency of the scheme by employing a threshold based approach to restore a node's accusation ability and to ensure sufficient normal nodes to accuse malicious nodes in MANETs. Extensive simulations show that the new method can effectively improve the performance of certificate revocation.
     

Sat: A Security Architecture Achieving Anonymity And Traceability In Wireless Mesh Networks (2011)

ABSTRACT

     

Efficient Public Key Certificate Management for Mobile Ad Hoc Networks (2011)

ABSTRACT
Mobile ad hoc networks involve communications over a shared wireless channel without any centralized infrastructure. Consequently, in an optimal solution, management and security services depend exclusively on network members. The main contribution of this paper is an efficient public key management scheme that is suitable for fully self-organized mobile ad hoc networks where all nodes play identical roles. Our approach implies that the operations of creating, storing, distributing, and revoking nodes' public keys are carried out locally by the nodes themselves. The goal of the presented methods is the improvement in the process of building local certificate repositories of nodes. In order to do it, an authentication solution based on the web of trust concept is combined with an element of routing based on the multipoint relay concept introduced in the optimized link state routing protocol


     

An Efficient Paging Scheme for Terminal Mobility using Personal Mobility Management Information in Interworked Fixed and Mobile Networks  (2011)

ABSTRACT
In interworked fixed and mobile networks, both terminal mobility (TM) and personal mobility (PM) should be supported and interworked to provide seamless universal mobility to mobile users. TM supports movement between different locations with the same mobile terminal (MT). In TM management, an MT updates its location when it changes location area (LA) and an incoming call is delivered to the MT by paging all cells within a registered LA. PM supports user mobility between different terminals by using personal identifier (PID). PM registration information of users is managed at registrar and an incoming call is delivered to the registered terminal based on registration information at registrar. Since location management in TM generates a lot of signaling messages over radio interface and consumes scarce radio resources, it is essential to reduce the number of location registration and paging signaling messages, i.e., signaling load. In this paper, we propose an efficient paging scheme for TM in interworked fixed and mobile networks, by using registration information for PM management. In the proposed paging scheme, paging is firstly performed only to the cells containing terminals with which a user is registered for PM, instead of all cells within a registered LA. If the called user is not found in the first paging step, remaining cells within the registered LA are paged. Performance comparison results show that the proposed scheme can achieve significant signaling load reduction at radio interface, and save scarce radio resources


     

Denial of Service Attacks in Wireless Networks: The Case of Jammers (2011)

ABSTRACT
The shared nature of the medium in wireless networks makes it easy for an adversary to launch a Wireless Denial of Service (WDoS) attack. Recent studies, demonstrate that such attacks can be very easily accomplished using off-the shelf equipment. To give a simple example, a malicious node can continually transmit a radio signal in order to block any legitimate access to the medium and/or interfere with reception. This act is called jamming and the malicious nodes are referred to as jammers. Jamming techniques vary from simple ones based on the continual transmission of interference signals, to more sophisticated attacks that aim at exploiting vulnerabilities of the particular protocol used. In this survey, we present a detailed up-to-date discussion on the jamming attacks recorded in the literature. We also describe various techniques proposed for detecting the presence of jammers. Finally, we survey numerous mechanisms which attempt to protect the network from jamming attacks. We conclude with a summary and by suggesting future directions


     

Dynamic Channel Allocation for Wireless Zone-Based Multicast and Broadcast Service (2011)

ABSTRACT
In wireless Multicast Broadcast Service (MBS), the common channel is used to multicast the MBS content to the Mobile Stations (MSs) on the MBS calls within the coverage area of a Base Station (BS), which causes interference to the dedicated channels serving the traditional calls, and degrades the system capacity. The MBS zone technology is proposed in Mobile Communications Network (MCN) standards to improve system capacity and reduce the handoff delay for the wireless MBS calls. In the MBS zone technology, a group of BSs form an MBS zone, where the macro diversity is applied in the MS, the BSs synchronize to transmit the MBS content on the same common channel, interference caused by the common channel is reduced, and the MBS MSs need not perform handoff while moving between the BSs in the same MBS zone. However, when there is no MBS MS in a BS with the MBS zone technology, the transmission on the common channel wastes the bandwidth of the BS. It is an important issue to determine the condition for the MBS Controller (MBSC) to enable the MBS zone technology by considering the QoS for traditional calls and MBS calls. In this paper, we propose two Dynamic Channel Allocation schemes: DCA and EDCA by considering the condition for enabling the MBS zone technology. Analysis and simulation experiments are conducted to investigate the performance of DCA and EDCA.


     

Intrusion detection: An Energy efficient approach in Heterogeneous WSN  (2011)

ABSTRACT
Intrusion detection plays an important role in the area of security in WSN. Detection of any type of intruder is essential in case of WSN. WSN consumes a lot of energy to detect an intruder. Therefore we derive an algorithm for energy efficient external and internal intrusion detection. We also analyse the probability of detecting the intruder for heterogeneous WSN. This paper considers single sensing and multi sensing intruder detection models. It is found that our experimental results validate the theoretical results
     

Wireless Sensor Networks: A Study on Congestion Routing Algorithms  (2011)

ABSTRACT
Data's generated in Wireless Sensor Networks may not all alike, some data's are more important than other data's and they may have different delivery requirements. If congestion occurs in the Wireless Network, some or more important data's may be dropped. But in our project we handle this problem by addressing differentiated delivery requirements. We propose a class of algorithms that enforce differentiated routing based on the congested areas of a network and data priority. The basic protocol, called Congestion-Aware Routing (CAR), discovers the congested zone of the network that exists between high-priority data sources and the data sink and, using simple forwarding rules, dedicates this portion of the network to forwarding primarily high-priority traffic. Since CAR requires some overhead for establishing the high-priority routing zone, it is unsuitable for highly mobile data sources. To accommodate these, we define MAC-Enhanced CAR (MCAR), which includes MAC-layer enhancements and a protocol for forming high priority paths on the fly for each burst of data. MCAR effectively handles the mobility of high-priority data sources, at the expense of degrading the performance of low-priority traffic
     

Design and Performance Analysis of Mobility Management Schemes Based on Pointer Forwarding for Wireless Mesh Networks (2011)

ABSTRACT
We propose efficient mobility management schemes based on pointer forwarding for wireless mesh networks (WMNs) with the objective to reduce the overall network traffic incurred by mobility management and packet delivery. The proposed schemes are per-user-based, i.e., the optimal threshold of the forwarding chain length that minimizes the overall network traffic is dynamically determined for each individual mobile user, based on the user's specific mobility and service patterns. We develop analytical models based on stochastic Petri nets to evaluate the performance of the proposed schemes. We demonstrate that there exists an optimal threshold of the forwarding chain length, given a set of parameters characterizing the specific mobility and service patterns of a mobile user. We also demonstrate that our schemes yield significantly better performance than schemes that apply a static threshold to all mobile users. A comparative analysis shows that our pointer forwarding schemes outperform routing-based mobility management protocols for WMNs, especially for mobile Internet applications characterized by large traffic asymmetry for which the downlink packet arrival rate is much higher than the uplink packet arrival rate.


     

Always Acyclic Distributed Path Computation (2010)

ABSTRACT
Distributed routing algorithms may give rise to transient loops during path recomputation, which can pose significant stability problems in high-speed networks. We present a new algorithm, Distributed Path Computation with Intermediate Variables (DIV), which can be combined with any distributed routing algorithm to guarantee that the directed graph induced by the routing decisions remains acyclic at all times. The key contribution of DIV, besides its ability to operate with any routing algorithm, is an update mechanism using simple message exchanges between neighboring nodes that guarantees loop-freedom at all times. DIV provably outperforms existing loop-prevention algorithms in several key metrics such as frequency of synchronous updates and the ability to maintain paths during transitions. Simulation results quantifying these gains in the context of shortest path routing are presented. In addition, DIV’s universal applicability is illustrated by studying its use with a routing that operates according to a non shortest path objective. Specifically, the routing seeks robustness against failures by maximizing the number of next-hops available at each node for each destination


     

>Bandwidth Recycling in IEEE 802.16 Networks (2010)

ABSTRACT
IEEE 802.16 standard was designed to support the bandwidth demanding applications with quality of service (QoS). Bandwidth is reserved for each application to ensure the QoS. For variable bit rate (VBR) applications, however, it is difficult for the subscriber station (SS) to predict the amount of incoming data. To ensure the QoS guaranteed services, the SS may reserve more bandwidth than its demand. As a result, the reserved bandwidth may not be fully utilized all the time. In this paper, we propose a scheme, named Bandwidth Recycling, to recycle the unused bandwidth without changing the existing bandwidth reservation. The idea of the proposed scheme is to allow other SSs to utilize the unused bandwidth when it is available. Thus, the system throughput can be improved while maintaining the same QoS guaranteed services. Mathematical analysis and simulation are used to evaluate the proposed scheme. Simulation and analysis results confirm that the proposed scheme can recycle 35% of unused bandwidth on average. By analyzing factors affecting the recycling performance, three scheduling algorithms are proposed to improve the overall throughput. The simulation results show that our proposed algorithm improves the overall throughput by 40% in a steady network.


     

A Pyramidal Security Model for Large-Scale Group-Oriented Computing in Mobile Ad Hoc Networks: The Key Management Study (2009)

ABSTRACT
In mobile ad hoc networks (MANETs), many applications require group-oriented computing among a large number of nodes in an adversarial environment. To deploy these large scale cooperative applications, secure multicast service must be provided to efficiently and safely exchange data among nodes. The existing literature has extensively studied security protection for a single multicast group, in which all nodes are assumed to have the same security level. However, such an assumption may not be valid in practice because, for many applications, different users can play different roles and thus naturally be classified into multiple security levels. A pyramidal security model to safeguard the multi security-level information sharing in one cooperation domain.


     

Continuous Monitoring of Spatial Queries in Wireless Broadcast Environments (2009)

ABSTRACT
Wireless data broadcast is a promising technique for information dissemination that leverages the computational capabilities of the mobile devices in order to enhance the scalability of the system. Under this environment, the data are continuously broadcast by the server, interleaved with some indexing information for query processing. Partners may then tune in the broadcast channel and process their queries locally without contacting the server. Previous work on spatial query processing for wireless broadcast systems has only considered snapshot queries over static data. In this paper, we propose an air indexing framework that 1) Outperforms the existing (i.e., snapshot) techniques in terms of energy consumption while achieving low access latency and 2) Constitutes the first method supporting efficient
     

Energy Maps for Mobile Wireless Networks: Coherence Time versus Spreading Period (2009)

ABSTRACT
We show that even though mobile networks are highly unpredictable when viewed at the individual node scale, the end-to-end quality-of-service metrics can be stationary when the mobile network is viewed in the aggregate. We define the coherence time as the maximum duration for which the end-to-end QoS metric remains roughly constant, and the spreading period as the minimum duration required to spread QoS information to all the nodes. We show that if the coherence time is greater than the spreading period, the end-to-end QoS metric can be tracked. We focus on the energy consumption as the end-to-end QoS metric, and describe a novel method by which an energy map can be constructed and refined in the joint memory of the mobile nodes. Finally, we show how energy maps can be utilized by an application that aims to minimize a node's total energy consumption over its near-future trajectory.


     

Mitigation of Control Channel Jamming Under Node Capture Attacks (2009)

ABSTRACT
Availability of service in many wireless networks depends on the ability for network users to establish and maintain communication channels using control messages from base stations and other users. An adversary with knowledge of the underlying communication protocol can mount an efficient denial of service attack by jamming the communication channels used to exchange control messages. The use of spread spectrum techniques can deter an external adversary from such control channel jamming attacks. However, malicious colluding insiders or an adversary who captures or compromises system users is not deterred by spread spectrum, as they know the required spreading sequences. For the case of internal adversaries, we propose a framework for control channel access schemes using the random assignment of cryptographic keys to hide the location of control channels. We propose and evaluate metrics to quantify the probabilistic availability of service under control channel jamming by malicious or compromised users and show that the availability of service degrades gracefully as the number of colluding insiders or compromised users increases. We propose an algorithm called GUIDE for the identification of compromised users in the system based on the set of control channels that are jammed. We evaluate the estimation error using the GUIDE algorithm in terms of the false alarm and miss rates in the identification problem. We discuss various design trade-offs between robustness to control channel jamming and resource expenditure.


     

Mobility Management Approaches for Mobile IP Networks (2009)

ABSTRACT
In wireless networks, efficient management of mobility is a crucial issue to support mobile users. The Mobile Internet Protocol (MIP) has been proposed to support global mobility in IP networks. Several mobility management strategies have been proposed which aim reducing the signaling traffic related to the Mobile Terminals (MTs) registration with the Home Agents (HAs) whenever their Care-of-Addresses (CoAs) change. They use different Foreign Agents (FAs) and Gateway FAs (GFAs) hierarchies to concentrate the registration processes. For high-mobility MTs, the Hierarchical MIP (HMIP) and Dynamic HMIP (DHMIP) strategies localize the registration in FAs and GFAs, yielding to high-mobility signaling. The Multicast HMIP strategy limits the registration processes in the GFAs. For high-mobility MTs, it provides lowest mobility signaling delay compared to the HMIP and DHMIP approaches. However, it is resource consuming strategy unless for frequent MT mobility. Hence, we propose an analytic model to evaluate the mean signaling delay and the mean bandwidth per call according to the type of MT mobility. In our analysis, the MHMIP Outperforms the DHMIP and MIP strategies in almost all the studied cases. The main contribution of this paper is the analytic model that allows the mobility management approaches performance evaluation


     

Bandwidth Efficient Video Multicasting in multi Cellular Wireless networks (2008)

ABSTRACT
In this paper, we propose a new mechanism to select the cells and the wireless technologies for layer-encoded video multicasting in the heterogeneous wireless networks. Different from the previous mechanisms, each mobile host in our mechanism can select a different cell with a different wireless technology to subscribe each layer of a video stream, and each cell can deliver only a subset of layers of the video stream to reduce the bandwidth consumption. We formulate the Cell and Technology Selection Problem (CTSP) to multicast each layer of a video stream as an optimization problem. We use Integer Linear Programming to model the problem and show that the problem is NP-hard. To solve the problem, we propose a distributed algorithm based on Lagrangean relaxation and a protocol based on the proposed algorithm. Our mechanism requires no change of the current video multicasting mechanisms and the current wireless network infrastructures. Our algorithm is adaptive not only to the change of the subscribers at each layer, but also the change of the locations


     

Bandwidth Estimation for IEEE 802.11-Based Ad Hoc Networks (2008)

ABSTRACT
Since 2005, IEEE 802.11-based networks have been able to provide a certain level of quality of service (QoS) by the means of service differentiation, due to the IEEE 802.11e amendment. However, no mechanism or method has been standardized to accurately evaluate the amount of resources remaining on a given channel. Such an evaluation would, however, be a good asset for bandwidth-constrained applications. In multi hop ad hoc networks, such evaluation becomes even more difficult. Consequently, despite the various contributions around this research topic, the estimation of the available bandwidth still represents one of the main issues in this field. In this paper, we propose an improved mechanism to estimate the available bandwidth in IEEE 802.11-based ad hoc networks. Through simulations, we compare the accuracy of the estimation we propose to the estimation performed by other state-of-the-art QoS protocols, BRuIT, AAC, and QoS-AODV.


     

Large Connectivity for Dynamic Random Geometric Graphs  (2008)

ABSTRACT
We provide the first rigorous analytical results for the connectivity of dynamic random geometric graphs a model for mobile wireless networks in which vertices move in random directions in the unit torus. We provide precise asymptotic results for the expected length of the connectivity and disconnectivity periods of the network. We believe that the formal tools developed in this work could be extended to be used in more concrete settings and in more realistic models, in the same manner as the development of the connectivity threshold for static random geometric graphs has affected a lot of research done on ad hoc networks.


     

Intrusion Detection in Homogeneous and Heterogeneous Wireless Sensor Networks (2008)

ABSTRACT
Intrusion detection in Wireless Sensor Network (WSN) is of practical interest in many applications such as detecting an intruder in a battlefield. The intrusion detection is defined as a mechanism for a WSN to detect the existence of inappropriate, incorrect, or anomalous moving attackers. In this paper, we consider this issue according to heterogeneous WSN models. Furthermore, we consider two sensing detection models: single-sensing detection and multiple-sensing detection... Our simulation results show the advantage of multiple sensor heterogeneous WSNs.


     

Location Based Spatial Query Processing In Wireless Broadcast Environments (2008)

ABSTRACT
Location-based spatial queries (LBSQ s) refer to spatial queries whose answers rely on the location of the inquirer. Efficient processing of LBSQ s is of critical importance with the ever-increasing deployment and use of mobile technologies. We show that LBSQ s has certain unique characteristics that the traditional spatial query processing in centralized databases does not address. For example, a significant challenge is presented by wireless broadcasting environments, which have excellent scalability but often exhibit high-latency database access. In this paper, we present a novel query processing technique that, though maintaining high scalability and accuracy, manages to reduce the latency considerably in answering LBSQ s. Our approach is based on peer-to-peer sharing, which enables us to process queries without delay at a mobile host by using query results cached in its neighboring mobile peers. We demonstrate the feasibility of our approach through a probabilistic analysis, and we illustrate the appeal of our technique through extensive simulation results.
     

Mitigating Performance Degradation in Congested Sensor Networks (2008)

ABSTRACT
Datas generated in Wireless Sensor Networks may not all alike, some Datas are more important than other Datas and they may have Different Delivery Requirements. If Congestion occurs in the Wireless Network. Some or More Important datas may be dropped. But in our Project we handle this problem by addressing Differentiated Delivery Requirements. We propose a class of algorithms that enforce differentiated routing based on the congested areas of a network and data priority. The basic protocol, called Congestion-Aware Routing (CAR), discovers the congested zone of the network that exists between high-priority data sources and the data sink and, using simple forwarding rules, dedicates this portion of the network to forwarding primarily high-priority traffic. Since CAR requires some overhead for establishing the high-priority routing zone, it is unsuitable for highly mobile data sources. To accommodate these, we define MAC-Enhanced CAR (MCAR), which includes MAC-layer enhancements and a protocol for forming high-priority paths on the fly for each burst of data. MCAR effectively handles the mobility of high-priority data sources, at the expense of degrading the performance of low-priority traffic.


     

Binary Tree Based Public-Key Management for Mobile Ad Hoc Networks (2008)

ABSTRACT
The establishment of a Public Key Infrastructure (PKI) in Mobile Ad Hoc Networks (MANETs) is considered a difficult task because of the intrinsic characteristics of these networks. The absence of centralized services and the possible network partitions make traditional security solutions not straightforwardly applicable in MANETs. In this project, we propose a public key management scheme based on a binary tree formation of the network's nodes. Using the binary tree structure, certificate chains are easily built between communicating nodes that are multi-hops away and the cumbersome problem of certificate chain discovery is avoided.


     

An Acknowledgment-Based Approach For The Detection Of Routing Misbehavior In MANETs (2007)

ABSTRACT
As attackers use automated methods to inflict widespread damage on vulnerable systems connected to the network, it has become painfully clear that traditional manual methods of protection do not suffice. This paper discusses an intrusion prevention approach, intrusion detection, response based on active networks that helps to provide rapid response to vulnerability advisories. An intrusion detection and intrusion blocker that can provide interim protection against a limited and changing set of high-likelihood or high-priority threats. It is expected that this mechanism would be easily and adaptively configured and deployed to keep pace with the ever-evolving threats on the network, intrusion detection and response based on agent system, digital signature used to provide a security. Active networks are an exciting development in networking services in which the infrastructure provides customizable network services to packets. The custom network services can be deployed by the user inside the packets themselves. In this paper we propose the use of agent based intrusion detection and response. Agents are integrated with the collaborative IDS in order to provide them with a wider array of information to use their response activities


     

Distributed Cache updating for the Dynamic source routing protocol (2006)

ABSTRACT
On-demand routing protocols use route caches to make routing decisions. Due to mobility, cached routes easily become stale. To address the cache staleness issue, prior work in DSR used heuristics with ad hoc parameters to predict the lifetime of a link or a route. The goal of our project is to proactively disseminating the broken link information to the nodes that have that link in their caches. We define a new cache structure called a cache table and present a distributed cache update algorithm. Each node maintains in its cache table the information necessary for cache updates. When a link failure is detected, the algorithm notifies all reachable nodes that have cached the link in a distributed manner. We show that the algorithm outperforms DSR with path caches and with Link-Max Life, an adaptive timeout mechanism for link caches. We conclude that proactive cache updating is key to the adaptation of on-demand routing protocols to mobility.
     

Benefit Based Data Caching In Ad Hoc Networks  (2006)

ABSTRACT
Data caching can significantly improve the efficiency of information access in a wireless ad hoc network by reducing the access latency and bandwidth usage. However, designing efficient distributed caching algorithms is on trivial when network nodes have limited memory. In this article, we consider the cache placement problem of minimizing total data access cost in ad hoc networks with multiple data items and nodes with limited memory capacity. The above optimization problem is known to be NP-hard. Defining benefit as the reduction in total access cost, we present a polynomial-time centralized approximation algorithm that provably delivers a solution whose benefit is at least 1/4 (1/2 for uniform-size data items) of the optimal benefit. The approximation algorithm is amenable to localized distributed implementation, which is shown via simulations to perform close to the approximation algorithm. Our distributed algorithm naturally extends to networks with mobile nodes. We simulate our distributed algorithm using a network simulator and demonstrate that it significantly outperforms another existing caching technique in all important performance metrics. The performance differential is particularly large in more challenging scenarios such as higher access frequency and smaller.
     

An Efficient Fault-Tolerant Distributed Channel Allocation Algorithm for Cellular Networks (2005)

ABSTRACT
A channel allocation algorithm in a cellular network consists of two parts: a channel acquisition algorithm and a channel selection algorithm. Some of the previous works in this field focused on centralized approaches to allocating channels. But, centralized approaches are neither scalable nor reliable. Recently, distributed dynamic channel allocation algorithms have been proposed, and they have gained a lot of attention due to their high reliability and scalability. But, in most of the algorithms, the cell that wants to borrow a channel has to wait for replies from all its interference neighbors and, hence, is not fault-tolerant. In this paper, we propose a new algorithm that is fault-tolerant and makes full use of the available channels. It can tolerate the failure of mobile nodes as well as static nodes without any significant degradation in service.


     

Mesh Based Multicast Routing in MANET: Stable Link Based Approach 2010

ABSTRACT
The group-oriented services are one of the primary application classes that are addressed by mobile ad hoc networks (MANETs) in recent years. To support such services, multicast routing is used. Thus, there is a need to design stable and reliable multicast routing protocols for MANETs to ensure better packet delivery ratio, lower delays and reduced control overheads. In this paper, we propose a mesh based multicast routing scheme that finds stable multicast path from source to receivers. The multicast mesh is constructed by using route request and route reply packets with the help of multicast routing information cache and link stability database maintained at every node. The stable paths are found based on selection of stable forwarding nodes that have high stability of link connectivity. The link stability is computed by using the parameters such as received power, distance between neighboring nodes and the link quality assessed using bit errors in a packet. The proposed scheme is simulated over a large number of MANET nodes with wide range of mobility and the performance is evaluated. It is observed that proposed scheme produces better packet delivery ratio, less control overheads and reduced packet delay compared to on-demand multicast routing protocol (ODMRP).
     

A Pyramidal Security Model for Large-Scale Group-Oriented Computing in Mobile Ad Hoc Networks: The Key Management Study 2009

ABSTRACT
In mobile ad hoc networks (MANETs), many applications require group-oriented computing among a large number of nodes in an adversarial environment. To deploy these large scale cooperative applications, secure multicast service must be provided to efficiently and safely exchange data among nodes. The existing literature has extensively studied security protection for a single multicast group, in which all nodes are assumed to have the same security level. However, such an assumption may not be valid in practice because, for many applications, different users can play different roles and thus naturally be classified into multiple security levels. A pyramidal security model to safeguard the multi security-level information sharing in one cooperation domain. As a prominent feature, a pyramidal security model contains a set of hierarchical security groups and multicast groups. To find an efficient key management solution that covers all the involved multicast groups, we develop the following three schemes for the proposed security model: 1) separated star key graph; 2) separated tree key graph, and 3) integrated tree key graph. Performance comparison demonstrates that the scheme of integrated tree key graph has advantages over its counterparts.
     

Effects of Location Awareness on Concurrent Transmissions for Cognitive Ad Hoc Networks Overlaying Infrastructure-Based Systems 2009

ABSTRACT
Through wideband spectrum sensing, cognitive radio (CR) can identify the opportunity of reusing the frequency spectrum of other wireless systems. To save time and energy of wideband spectrum, we investigate to what extent a CR system incorporating the location awareness capability can establish a scanning-free region where a peer-to-peer ad hoc network can overlay on an infrastructure-based network. Based on the carrier sense multiple access with collision avoidance (CSMA/CA) medium access control (MAC) protocol, the concurrent transmission probability of a peer-to-peer connection and an infrastructure-based connection is computed. It is shown that the frequency band of the legacy system can be reused up to 45 percent by the overlaying cognitive ad hoc network when CR users have the location information of the primary and secondary users.
     

An Efficient Genetic Algorithm for the Bandwidth Calculation Problem in TDMA-based Mobile Ad Hoc Networks 2007

ABSTRACT
Most of the existing routing algorithms/protocols in mobile ad hoc networks (MANETs) have been designed primarily to carry best-effort traffic and only concerned with shortest-path routing. Little attention is paid to the issues related to the quality-of-service (QoS) requirements of a path. In this study, searching for a path to satisfy bandwidth requirements in a time-division multiple-access-based (TDMA–based) MANET has been the main goal. This is an NP-complete problem. The genetic algorithm (GA) has been successfully applied to many well-known NP complete problems in communication networks, such as the multicast routing problem. In this study, the principle of GA is used to design an efficient heuristic algorithm, which is executed in a centralized manner, for the bandwidth calculation (BWC) problem in a TDMA-based MANET. Extensive computer simulations are performed to compare the performance of the proposed GA with that of another heuristic algorithm. Simulation results verify that the GA can produce a larger bandwidth.
     

A Distributed Algorithm for Finding All Best Swap Edges of a Minimum Diameter Spanning Tree (2011)

ABSTRACT
Communication in networks suffers if a link fails. When the links are edges of a tree that has been chosen from an underlying graph of all possible links, a broken link even disconnects the network. Most often, the link is restored rapidly. A good policy to deal with this sort of transient link failures is swap rerouting, where the temporarily broken link is replaced by a single swap link from the underlying graph. A rapid replacement of a broken link by a swap link is only possible if all swap links have been precomputed. The selection of high quality swap links is essential; it must follow the same objective as the originally chosen communication subnetwork. We are interested in a minimum diameter tree in a graph with edge weights (so as to minimize the maximum travel time of messages). Hence, each swap link must minimize (among all possible swaps) the diameter of the tree that results from swapping. We propose a distributed algorithm that efficiently computes all of these swap links, and we explain how to route messages across swap edges with a compact routing scheme. Finally, we consider the computation of swap edges in an arbitrary spanning tree, where swap edges are chosen to minimize the time required to adapt routing in case of a failure, and give efficient distributed algorithms for two variants of this problem.
     

Location Aided Flat Hybrid Routing Protocol (2011)

ABSTRACT
Routing protocols for mobile ad hoc networks can be classified into two categories: topological routing and geographic routing. However, most of the existing protocols use only one routing strategy for different types of networks. Routing protocols that give good performance for sparse networks may not perform well in dense networks. Routing protocols that are suitable for small networks may not scale well in large networks. Due to the fact hybrid routing protocols based on the benefits of both schemes have attracted a lot of attention recently. Proposed protocol is a hybrid routing protocol that provides a hybrid solution of topological and geographic routing. The protocol is a flat routing protocol in spite of using the partitions. Incorporation of long hop routing (smaller number of longer hops) reduces the number of nodes on the route and hence also the overhead involved. It employs swarm intelligence location service to find out the location of a destination instead of exploiting the flooding, thus overcome from a number of related problems like low scalability, more overheads, energy and bandwidth usage, single point failure and network congestion. With the help of location information it forwards the packet directionally towards the destination.


     

A distributed protocol to serve dynamic groups for peer-to-peer streaming (2010)

ABSTRACT
Peer-to-peer (P2P) streaming has been widely deployed over the Internet. A streaming system usually has multiple channels, and peers may form multiple groups for content distribution. In this paper, we propose a distributed overlay framework (called SMesh) for dynamic groups where users may frequently hop from one group to another while the total pool of users remain stable. SMesh first builds a relatively stable mesh consisting of all hosts for control messaging. The mesh supports dynamic host joining and leaving, and will guide the construction of delivery trees. Using the Delaunay Triangulation (DT) protocol as an example, we show how to construct an efficient mesh with low maintenance cost. We further study various tree construction mechanisms based on the mesh, including embedded, bypass, and intermediate trees. Through simulations on Internet-like topologies, we show that SMesh achieves low delay and low link stress.


     

Cooperative Caching in Wireless P2P Networks: Design, Implementation, And Evaluation (2010)

ABSTRACT
Some recent studies have shown that cooperative cache can improve the system performance in wireless P2P networks such as ad hoc networks and mesh networks. However, all these studies are at a very high level, leaving many design and implementation issues unanswered. In this paper, we present our design and implementation of cooperative cache in wireless P2P networks, and propose solutions to find the best place to cache the data. We propose a novel asymmetric cooperative cache approach, where the data requests are transmitted to the cache layer on every node, but the data replies are only transmitted to the cache layer at the intermediate nodes that need to cache the data


     

Multipath Dissemination In Regular Mesh Topologies (2009)

ABSTRACT
Mesh topologies are important for large-scale peer-to-peer systems that use low-power transceivers. The Quality of Service (QoS) in such systems is known to decrease as the scale increases. We present a scalable approach for dissemination that exploits all the shortest paths between a pair of nodes and improves the QoS. Despite the presence of multiple shortest paths in a system, we show that these paths cannot be exploited by spreading the messages over the paths in a simple round-robin manner; nodes along one of these paths will always handle more messages than the nodes along the other paths.


     

Virtual-Force-Based Geometric Routing Protocol in MANETs (2009)

ABSTRACT
Routing is the foremost issue in mobile ad hoc networks (MANETs). To guarantee delivery and improve performance, most position-based routing protocols, e.g., greedy-face-greedy (GFG), forward a message in greedy routing mode until the message is forwarded to a local minimum where greedy forwarding is impossible. They then switch to a less efficient mode known as face routing. Face routing requires the underlying network to be a planar graph which makes geometric routing only theoretically feasible. To remove this constraint, this project tackles the local minimum problem with two new methods. First, we construct a virtual small-world network by adding virtual long links to the network to reduce the number of local minima. Second, we use the virtual force method to recover from local minima without relying on face routing. Combining these two methods, we propose a purely greedy routing protocol, the small-world iterative navigation greedy (SWING+) routing protocol. Simulations are conducted to evaluate SWING+ against existing geometric routing protocols. Simulation results show that SWING+ guarantees delivery, and that its performance is comparable to that of the state-of-the-art greedy other adaptive face routing (GOAFR+) routing protocol


     

Detecting Malicious Packet Losses 

ABSTRACT
The problem of detecting whether a compromised router is maliciously manipulating its stream of packets. In particular, we are concerned with a simple yet effective attack in which a router selectively drops packets destined for some victim. Unfortunately, it is quite challenging to attribute a missing packet to a malicious action because normal network congestion can produce the same effect. Modern networks routinely drop packets when the load temporarily exceeds their buffering capacities. Previous detection protocols have tried to address this problem with a user-defined threshold: too many dropped packets imply malicious intent. However, this heuristic is fundamentally unsound; setting this threshold is, at best, an art and will certainly create unnecessary false positives or mask highly focused attacks. We have designed, developed, and implemented a compromised router detection protocol that dynamically infers, based on measured traffic rates and buffer sizes, the number of congestive packet losses that will occur. Once the ambiguity from congestion is removed, subsequent packet losses can be attributed to malicious actions. We have tested our protocol in EMU lab and have studied its effectiveness in differentiating attacks from legitimate network behavior.


     

Distributed Algorithms for Constructing Approximate Minimum Spanning (2009)

ABSTRACT
While there are distributed algorithms for the minimum spanning tree (MST) problem, these algorithms require relatively large number of messages and time, and are fairly involved, making them impractical for resource-constrained networks such as wireless sensor networks. In such networks, a sensor has very limited power, and any algorithm needs to be simple, local, and energy efficient. Motivated by these considerations, we design and analyze a class of simple and local distributed algorithms called Nearest Neighbor Tree (NNT) algorithms for energy-efficient construction of an approximate MST in wireless networks. Assuming that the nodes are uniformly distributed, we show provable bounds on both the quality of the spanning tree produced and the energy needed to construct them. We show that while NNT produces a close approximation to the MST, it consumes asymptotically less energy than the classical message-optimal distributed MST algorithm due to Gallagery, Humblet, and Spira. Further, the NNTs can be maintained dynamically with polylogarithmic rearrangements under node insertions/deletions. We also perform extensive simulations, which show that the bounds are much better in practice. Our results, to the best of our knowledge, demonstrate the first tradeoff between the quality of approximation and the energy required for building spanning trees on wireless networks, and motivate similar considerations for other important problems.
     

Dynamic Routing with Security Considerations (2009)

ABSTRACT
Security has become one of the major issues for data communication over wired and wireless networks. Different from the past work on the designs of cryptography algorithms and system infrastructures, An analytic study on the proposed algorithm is presented, and experiments are conducted to verify the analytic results and to show the capability of the proposed algorithm.


     

Dynamic Search Algorithm in Unstructured Peer-to-Peer Networks (2009)

ABSTRACT
Designing efficient search algorithms is a key challenge in unstructured peer-to-peer networks. Flooding and random walk (RW) are two typical search algorithms. Flooding searches aggressively and covers the most nodes. However, it generates a large amount of query messages and, thus, does not scale. On the contrary, RW searches conservatively. It only generates a fixed amount of query messages at each hop but would take longer search time. We propose the dynamic search (DS) algorithm, which is a generalization of flooding and RW. DS takes advantage of various contexts under which each previous search algorithm performs well. It resembles flooding for short-term search and RW for long-term search. Moreover, DS could be further combined with knowledge-based search mechanisms to improve the search performance. We analyze the performance of DS based on some performance metrics including the success rate, search time, query hits, query messages, query efficiency, and search efficiency. Numerical results show that DS provides a good tradeoff between search performance and cost. On average, DS performs about 25 times better than flooding and 58 times better than RW in power-law graphs, and about 186 times better than flooding and 120 times better than RW in bimodal topologies.


     

Effective and Efficient Query Processing for Video Subsequence Identification (2009)

ABSTRACT
This paper presents a graph transformation and matching approach to identify the occurrence of potentially different ordering or length due to content editing. With a novel batch query algorithm to retrieve similar frames, the mapping relationship between the query and database video is first represented by a bipartite graph. The densely matched parts along the long sequence are then extracted, followed by a filter-and-refine search strategy to prune some irrelevant subsequences. During the filtering stage, Maximum Size Matching is deployed for each sub graph constructed by the query and candidate subsequence to obtain a smaller set of candidates. During the refinement stage, Sub-Maximum Similarity Matching is devised to identify the subsequence with the highest aggregate score from all candidates, according to a robust video similarity model that incorporates visual content, temporal order, and frame alignment information


     

Flexible Deterministic Packet Marking: An IP Traceback System to Find the  (2009)

ABSTRACT
Internet Protocol (IP) Traceback is the enabling technology to control Internet crime. In this paper, we present a novel and practical IP traceback system called Flexible Deterministic Packet Marking (FDPM) which provides a defense system with the ability to find out the real sources of attacking packets that traverse through the network. While a number of other traceback schemes exist, FDPM provides innovative features to trace the source of IP packets and can obtain better tracing capability than others. In particular, FDPM adopts a flexible mark length strategy to make it compatible to different network environments; it also adaptively changes its marking rate according to the load of the participating router by a flexible flow-based marking scheme. Evaluations on both simulation and real system implementation demonstrate that FDPM requires a moderately small number of packets to complete the Traceback process; add little additional load to routers and can trace a large number of sources in one traceback process with low false positive rates. The built-in overload prevention mechanism makes this system capable of achieving a satisfactory traceback result even when the router is heavily loaded. The motivation of this traceback system is from DDoS defense. It has been used to not only trace DDoS attacking packets but also enhance filtering attacking traffic. It has a wide array of applications for other security systems.


     

Evaluating the Vulnerability of Network Traffic Using Joint Security and
Routing Analysis (2009)

ABSTRACT
Joint analysis of security and routing protocols in wireless networks reveals vulnerabilities of secure network traffic that remain undetected when security and routing protocols are analyzed independently. We formulate a class of continuous metrics to evaluate the vulnerability of network traffic as a function of security and routing protocols used in wireless networks. We discuss the availability of security parameters to the adversary and show that unknown parameters can be estimated using probabilistic analysis. We demonstrate vulnerability evaluation using the proposed metrics and node capture attacks using the GNAVE algorithm.


     

Computation-Efficient Multicast Key Distribution (2008)

ABSTRACT
Efficient key distribution is an important problem for secure group communications. The communication and storage complexity of multicast key distribution problem has been studied extensively. In this paper, we propose a new multicast key distribution scheme whose computation complexity is significantly reduced. Instead of using conventional encryption algorithms, the scheme employs MDS codes, a class of error control codes, to distribute multicast key dynamically. This scheme drastically reduces the computation load of each group member compared to existing schemes employing traditional encryption algorithms. Such a scheme is desirable for many wireless applications where portable devices or sensors need to reduce their computation as much as possible due to battery power limitations. Easily combined with any key-tree-based schemes, this scheme provides much lower computation complexity while maintaining low and balanced communication complexity and storage complexity for secure dynamic multicast key distribution


     

DCMP : A Distributed Cycle Minimization Protocol for Peer-to-Peer Networks  (2008)

ABSTRACT
In this project, we describe the Distributed Cycle Minimization Protocol (DCMP), a dynamic fully decentralized protocol that significantly reduces the duplicate messages by eliminating unnecessary cycles. As queries are transmitted through the peers, DCMP identifies the problematic paths and attempts to break the cycles while maintaining the connectivity of the network. In order to preserve the fault resilience and load balancing properties of unstructured P2P systems, DCMP avoids creating a hierarchical organization. Instead, it applies cycle elimination symmetrically around some powerful peers to keep the average path length small. The overall structure is constructed fast with very low overhead. With the information collected during this process, distributed maintenance is performed efficiently even if peers quit the system without notification. The experimental results from our simulator and the prototype implementation on Planet Lab confirm that DCMP significantly improves the scalability of unstructured P2P systems without sacrificing their desirable properties. Moreover, due to its simplicity, DCMP can be easily implemented in various existing P2P systems and is orthogonal to the search algorithms.


     

Efficient and Secure Content Processing and Distribution by Cooperative Intermediaries (2008)

ABSTRACT
Content services such as content filtering and trans coding adapt contents to meet system requirements, display capacities, or user preferences. Data security in such a framework is an important problem and crucial for many Web applications. In this paper, we propose an approach that addresses data integrity and confidentiality in content adaptation and caching by intermediaries. Our approach permits multiple intermediaries to simultaneously perform content services on different portions of the data. Our protocol supports decentralized proxy and key management and flexible delegation of services. Our experimental results show that our approach is efficient and minimizes the amount of data transmitted across the network.


     

Optimal State Allocation for Multicast Communication with Explicit Multicast forwarding (2008)

ABSTRACT
We propose a scalable and adaptive multicast forwarding mechanism based on Explicit Multicast (Xcast). This mechanism optimizes the allocation of forwarding states in routers and can be used to improve the scalability of traditional IP multicast and Source-Specific Multicast. We propose a new multicast forwarding mechanism based on Explicit Multicast (Xcast) forwarding for SSM and IP multicast. Our mechanism needs fewer routers in a multicast tree to store forwarding states and therefore leads to a more balanced distribution of forwarding states among routers. 1) The first problem, referred to as MINSTATE, minimizes the total number of Routers that store forwarding states in a multicast tree. 2) The second problem, referred to as BALANCESTATE, minimizes the maximum number of forwarding states stored in a router for all multicast groups, which is proved to be an NP-hard problem. We design a distributed algorithm that obtains the optimal solution to the first problem and propose an approximation algorithm for the second problem. Our mechanism can balance forwarding states stored among routers and reduce the number of routers that store the forwarding states for a multicast tree.


     

QUIVER Consistent Object Sharing For Edge Services (2008)

ABSTRACT
We present Quiver, a system that coordinates service proxies placed at the edge of the Internet to serve distributed Partners accessing a service involving mutable objects. Quiver enables these proxies to perform consistent accesses to shared objects by migrating the objects to proxies performing operations on those objects. These migrations dramatically improve performance when operations involving an object exhibit geographic locality, since migrating this object into the vicinity of proxies hosting these operations will benefit all such operations. This system reduces the workload in the server. It performs the all operations in the proxies itself. In this system the operations performed in First-In-First-Out process. This system handles two process serializability and strict serializability for durability in the consistent object sharing. Other workloads benefit from Quiver, dispersing the computation load across the proxies and saving the costs of sending operation parameters over the wide area when these are large. Quiver also supports optimizations for single-object reads that do not involving migrating the object. We detail the protocols for implementing object operations and for accommodating the addition, involuntary disconnection, and voluntary departure of proxies. Finally, we discuss the use of Quiver to build an e-commerce application and a distributed network traffic modeling service.


     

A Fully Distributed Proactively Secure Threshold-Multisignature Scheme (2007)

ABSTRACT
Threshold-multi signature schemes combine the properties of threshold group-oriented signature schemes and multi signature schemes to yield a signature scheme that allows a threshold or more group members to collaboratively sign an arbitrary message. In contrast to threshold group signatures, the individual signers do not remain anonymous, but are publicly identifiable from the information contained in the valid threshold-multi signature. The main objective of this paper is to propose such a secure and efficient threshold-multi signature scheme. The paper uniquely defines the fundamental properties of threshold multi signature schemes and shows that the proposed scheme satisfies these properties and eliminates the latest attacks to which other similar schemes are subject. The efficiency of the proposed scheme is analyzed and shown to be superior to its counterparts. The paper also proposes a discrete logarithm based distributed-key management infrastructure (DKMI), which consists of a round optimal, publicly verifiable, distributed-key generation (DKG) protocol and a one round, publicly verifiable, distributed-key redistribution/ updating (DKRU) protocol. The round optimal DKRU protocol solves a major problem with existing secret redistribution/updating schemes by giving group members a mechanism to identify malicious or faulty share holders in the first round, thus avoiding multiple protocol executions.


     

A New Operational Transformation Framework for Real-Time Group Editors (2007)

ABSTRACT
Group editors allow a group of distributed human users to edit a shared graphical document at the same time over a computer network. In this project a normal operation transformation framework is developed to efficiently share the text and graphical data to the different users or a particular user connected in the network. The basic idea of operation transformation is to execute any local operation as soon as it is generated for high local responsiveness. Remote operations are transformed against concurrent operations that have been executed locally before its execution. Operation transformation has been well accepted in group editors for achieve high local responsiveness and unconstrained collaboration. It is also well established method for optimistic consistency control. Operation transformation framework is established with formalizes two consistency criteria, causality preservation and convergence. The Operation transformation framework in this project is developed and the weaknesses of the existing system are overcome based on the concept called operation effects relation.


     

A Robust Spanning Tree Topology for Data Collection and Dissemination in Distributed Environments (2007)

ABSTRACT
Large-scale distributed applications are subject to frequent disruptions due to resource contention and failure. Such disruptions are inherently unpredictable and, therefore, robustness is a desirable property for the distributed operating environment. In this work, we describe and evaluate a robust topology for applications that operate on a spanning tree overlay network. Unlike previous work that is adaptive or reactive in nature, we take a proactive approach to robustness. The topology itself is able to simultaneously Withstand disturbances and exhibit good performance. We present both centralized and distributed algorithms to construct the topology, and then demonstrate its effectiveness through analysis and simulation of two classes of distributed applications: Data collection in sensor networks and data dissemination in divisible load scheduling. The results show that our robust spanning trees achieve a desirable trade-off for two opposing metrics where traditional forms of spanning trees do not. In particular, the trees generated by our Algorithms exhibit both resilience to data loss and low power consumption for sensor networks. When used as the overlay network for divisible load scheduling, they display both robustness to link congestion and low values for the make span of the schedule.


     

Dynamic Load Balancing in Distributed Systems in the Presence of Delays: A Regeneration-Theory Approach (2007)

ABSTRACT
The approach considers the heterogeneity in the processing rates of the nodes as well as the randomness in the delays imposed by the communication medium. The optimal one-shot load balancing policy is developed and subsequently extended to develop an autonomous and distributed load-balancing policy that can dynamically reallocate incoming external loads at each node. This adaptive and dynamic load balancing policy is implemented and evaluated in a two-node distributed system. The performance of the proposed dynamic load-balancing policy is compared to that of static policies as well as existing dynamic load-balancing policies by considering the average completion time per task and the system processing rate in the presence of random arrivals of the external loads.


     

Multicast Routing with Delay and Delay Variation Constraints for Collaborative Applications on Overlay Networks (2007)

ABSTRACT
Computer supported collaborative applications on overlay networks are gaining popularity among users who are geographically dispersed. Examples of these kinds of applications include video-conferencing, distributed database replication, and online games. This type of application requires a multicasting sub network, using which messages should arrive at the destinations within a specified delay bound. These applications also require that destinations receive the message from the source at approximately the same time. The problem of finding a multicasting sub network with delay and delay-variation bound has been proved to be an NP Complete problem in the literature and heuristics have been proposed for this problem. In this paper, we provide an efficient heuristic to obtain a multicast sub network on an overlay network, given a source and a set of destinations that is within a specified maximum delay and a specified maximum variation in the delays from a source to the destinations. We have shown that our algorithm is significantly better in terms of time-complexity than existing algorithms for the same problem. Our extensive empirical studies indicate that our heuristic uses significantly less runtime in comparison with the best-known heuristics while achieving the tightest delay variation for a given end-to-end delay bound


     

OCGRR: A New Scheduling Algorithm for Differentiated Services Networks (2007)

ABSTRACT
We propose a new fair scheduling technique, called OCGRR (Output Controlled Grant-based Round Robin), for the support of Diff Serve traffic in a core router. We define a stream to be the same-class packets from a given immediate upstream router destined to an output port of the core router. At each output port, streams may be isolated in separate buffers before being scheduled in a frame. The sequence of traffic transmission in a frame starts from higher-priority traffic and goes down to lower-priority traffic. A frame may have a number of small rounds for each class. Each stream within a class can transmit a number of packets in the frame based on its available grant, but only one packet per small round, thus reducing the inter transmission time from the same stream and achieving a smaller jitter and startup latency. The grant can be adjusted in a way to prevent the starvation of lower priority classes. We also verify and demonstrate the good performance of our scheduler by simulation and comparison with other algorithms in terms of queuing delay, jitter, and start-up latency.


     

Randomized Protocols for Duplicate Elimination in Peer to Peer Systems (2007)

ABSTRACT
Distributed peer-to-peer systems rely on voluntary participation of peers to effectively manage a storage pool. In such systems, data is generally replicated for performance and availability. If the storage associated with replication is not monitored and provisioned, the underlying benefits may not be realized. Resource constraints, performance scalability, and availability present diverse considerations. Availability and performance scalability, in terms of response time, are improved by aggressive replication, whereas resource constraints limit total storage in the network. Identification and elimination of redundant data pose fundamental problems for such systems. In this paper, we present a novel and efficient solution that addresses availability and scalability with respect to management of redundant data. Specifically, we address the problem of duplicate elimination in the context of systems connected over an unstructured peer-to-peer network in which there is no a priori binding between an object and its location. We propose two randomized protocols to solve this problem in a scalable and decentralized fashion that does not compromise the availability requirements of the application. Performance results using both large-scale simulations and a prototype built on Planet Lab demonstrate that our protocols provide high probabilistic guarantees while incurring minimal administrative overheads.


     

Predictive Job Scheduling in a Connection Limited System using Parallel Genetic Algorithm (2006)

ABSTRACT
Job scheduling is the key feature of any computing environment and the efficiency of computing depends largely on the scheduling technique used. Intelligence is the key factor which is lacking in the job scheduling techniques of today. Genetic algorithms are powerful search techniques based on the mechanisms of natural selection and natural genetics. Multiple jobs are handled by the scheduler and the resource the job needs are in remote locations. Here we assume that the resource a job needs are in a location and not split over nodes and each node that has a resource runs a fixed number of jobs.


     

Chunk distribution in Mesh-Based Large Scale P2P Streaming Systems: A fluid approach 2010

ABSTRACT
We consider large scale mesh-based P2P systems for the distribution of real-time video content. Our goal is to study the impact that different design choices adopted while building the overlay topology may entail on the system performance. In particular we show that the adoption of different strategies leads to overlay topologies with different macroscopic properties. Representing the possible overlay topologies with different families of random graphs, we develop simple yet accurate fluid models that capture the dominant dynamics of the chunk distribution process over several families of random graph. Our fluid models allow us to compare the performance of different strategies providing guidance for the design of new more efficient systems. In particular, we show that system performance can be significantly improve when possibly available information about peers location and/or peer access bandwidth is carefully exploited in the overlay topology formation process.
     

A Scalable Overlay Multicast Architecture for Large-Scale Applications 2007

ABSTRACT
In this paper, we propose a Two-tier Overlay Multicast Architecture (TOMA) to provide scalable and efficient multicast support for various group communication applications. In TOMA, Multicast Service Overlay Network (MSON) is advocated as the backbone service domain, while end users in access domains form a number of small clusters, in which an application-layer multicast protocol is used for the communication between the clustered end users. TOMA is able to provide efficient resource utilization with less control overhead, especially for large-scale applications. It also alleviates the state scalability problem and simplifies multicast tree construction and maintenance when there are large numbers of groups in the network. To help MSON providers efficiently plan backbone service overlay, we suggest several provisioning algorithms to locate proxies, select overlay links, and allocate link bandwidth. Extensive simulation studies demonstrate the promising performance of TOMA.
     

Face Recognition Using Laplacian faces (2005)

ABSTRACT
We propose an appearance-based face recognition method called the Laplacian face approach. By using Locality Preserving Projections (LPP), the face images are mapped into a face subspace for analysis. Different from Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) which effectively see only the Euclidean structure of face space, LPP finds an embedding that preserves local information, and obtains a face subspace that best detects the essential face manifold structure. The Laplacian faces are the optimal linear approximations to the Eigen functions of the Laplace Beltrami operator on the face manifold. In this way, the unwanted variations resulting from changes in lighting, facial expression, and pose may be eliminated or reduced. Theoretical analysis shows that PCA, LDA, and LPP can be obtained from different graph models. We compare the proposed Laplacian face approach with Eigen face and Fisher face methods on three different face data sets. Experimental results suggest that the proposed Laplacian face approach provides a better representation and achieves lower error rates in face recognition.


     

Online Handwritten Script Recognition (2004)

ABSTRACT
Automatic identification of handwritten script facilitates many important applications such as automatic transcription of multilingual documents and search for documents on the Web containing a particular script. The increase in usage of handheld devices which accept handwritten input has created a growing demand for algorithms that can efficiently analyze and retrieve handwritten data. This paper proposes a method to classify words and lines in an online handwritten document into one of the six major scripts: Arabic, Cyrillic, Devnagari, Han, Hebrew, or Roman. The classification is based on 11 different spatial and temporal features extracted from the strokes of the words. The proposed system attains an overall classification accuracy of 87.1 percent at the word level with 5-fold cross validation on a data set containing 13,379 words. The classification accuracy improves to 95 percent as the number of words in the test sample is increased to five, and to 95.5 percent for complete text lines consisting of an average of seven words.


     

A BGP-based Mechanism for Lowest-Cost Routing (2003)

ABSTRACT
The routing of traffic between Internet domains, or Autonomous Systems (ASs), a task known as Interdomain routing, is currently handled by the Border Gateway Protocol (BGP). In this paper, we address the problem of Interdomain routing from a mechanism-design point of view. The application of mechanism-design principles to the study of routing is the subject of earlier work by Nisan and Ronen and Hershberger and Suri. In this paper, we formulate and solve a version of the routing-mechanism design problem that is different from the previously studied version in three ways that make it more accurately reflective of real-world Interdomain routing: (1)We treat the nodes as strategic agents, rather than the links; (2)Our mechanism computes lowest-cost routes for all source-destination pairs and payments for transit nodes on all of the routes; (3)We show how to compute our mechanism with a distributed algorithm that is a straightforward extension to BGP and causes only modest increases in routing table size and convergence time. This approach of using an existing protocol as a substrate for distributed computation may prove useful in future development of Internet algorithms generally, not only for routing or pricing problems. Our design and analysis of a strategy proof, BGP-based routing mechanism provides a new, promising direction in distributed algorithmic mechanism design, which has heretofore been focused mainly on multicast cost sharing.


     

Neural Networks for Unicode optical Character Recognition (2006)

ABSTRACT
If we try to understand what exactly happens when we are reading, we will realize that when we see the printed paper an image gets formed on the retina of an eye, some signals are sent to the brain and the brain cells called neurons have something called as intelligence due to which they can recognize the characters. Now if we stimulate this behavior in software. The main aim of this project Training based Numeric Character Recognition using Neural Networks is for handwritten digit recognition by comparing with existing numeric images. In this project we mainly use two different techniques image processing and neural network technique.
A neural network is a massively parallel distributed processor made up of simple processing units, which has a natural propensity for storing experimental knowledge. In neural network knowledge refers to stored information or models used by a person or machine to interrupt, predict and appropriately respond to the output world.
     

Robust Video Data Hiding Using Forbidden Zone Data Hiding and Selective Embedding (2011)

ABSTRACT
Video data hiding is still an important research topic due to the design complexities involved. We propose a new video data hiding method that makes use of erasure correction capability of Repeat Accumulate codes and superiority of Forbidden Zone Data Hiding. Selective embedding is utilized in the proposed method to determine host signal samples suitable for data hiding. This method also contains a temporal synchronization scheme in order to withstand frame drop and insert attacks. The proposed framework is tested by typical broadcast material against MPEG-2, H.264 compression, frame-rate conversion attacks, as well as other well-known video data hiding methods. The decoding error values are reported for typical system parameters. The simulation results indicate that the framework can be successfully utilized in video data hiding applications.
     

Computational Perceptual Features for Texture Representation and Retrieval (2011)

ABSTRACT
A perception-based approach to content-based image representation and retrieval is proposed in this paper. We consider textured images and propose to model their textural content by a set of features having a perceptual meaning and their application to content-based image retrieval. We present a new method to estimate a set of perceptual textural features, namely coarseness, directionality, contrast, and busyness. The proposed computational measures can be based upon two representations: the original images representation and the autocorrelation function (associated with original images) representation. The set of computational measures proposed is applied to content-based image retrieval on a large image data set, the well-known Brodatz database. Experimental results and benchmarking show interesting performance of our approach. First, the correspondence of the proposed computational measures to human judgments is shown using a psychometric method based upon the Spearman rank-correlation coefficient. Second, the application of the proposed computational measures in texture retrieval shows interesting results, especially when using results fusion returned by each of the two representations. Comparison is also given with related works and show excellent performance of our approach compared to related approaches on both sides: correspondence of the proposed computational measures with human judgments as well as the retrieval effectiveness.
     

Optimal Bandwidth Assignment for Multiple-Description-Coded Video (2011)

ABSTRACT
In video streaming over multicast network, user bandwidth requirement is often heterogeneous possibly with orders of magnitude difference (say, from hundreds of kb/s for mobile devices to tens of Mb/s for high-definition TV). Multiple description coding (MDC) can be used to address this bandwidth heterogeneity issue. In MDC, the video source is encoded into multiple independent descriptions. A receiver, depending on its available bandwidth, joins different descriptions to meet their bandwidth requirements. An important but challenging problem for MDC video multicast is how to assign bandwidth to each description in order to maximize overall user satisfaction. In this paper, we investigate this issue by formulating it as an optimization problem, with the objective to maximize user bandwidth experience by taking into account the encoding inefficiency due to MDC. We prove that the optimization problem is NP-hard. However, if the description number is larger than or equal to a certain threshold (e.g., if the minimum and maximum bandwidth requirements are 100 kb/s and 10 Mb/s, respectively, such threshold is seven descriptions), there is an exact and simple solution to achieve maximum user satisfaction, i.e., meeting all the bandwidth requirements. For the case when the description number is smaller, we present an efficient heuristic called simulated annealing for MDC bandwidth assignment (SAMBA) to assign bandwidth to each description given the distribution of user bandwidth requirement. We evaluate our algorithm using simulations. SAMBA achieves virtually the same optimal performance based on exhaustive search. By comparing with other assignment algorithms, SAMBA significantly improves user satisfaction. We also show that, if the coding efficiency decreases with the number of descriptions, there is an optimal description number to achieve maximal user satisfaction.
     

Implementation of LSB Steganography and its Evaluation for Various File Formats  (2011)

ABSTRACT
Steganography is derived from the Greek word steganos which literally means “Covered” and graphy means “Writing”, i.e. covered writing. Steganography refers to the science of “invisible” communication. For hiding secret information in various file formats, there exists a large variety of steganographic techniques some are more complex than others and all of them have respective strong and weak points. The Least Significant Bit (LSB) embedding technique suggests that data can be hidden in the least significant bits of the cover image and the human eye would be unable to notice the hidden image in the cover file. This technique can be used for hiding images in 24-Bit, 8-Bit, Gray scale format. This paper explains the LSB Embedding technique and Presents the evaluation for various file formats.
     

Color Extended Visual Cryptography Using Error Diffusion (2011)

ABSTRACT
Color visual cryptography (VC) encrypts a color secret message into color halftone image shares. Previous methods in the literature show good results for black and white or gray scale VC schemes, however, they are not sufficient to be applied directly to color shares due to different color structures. Some methods for color visual cryptography are not satisfactory in terms of producing either meaningless shares or meaningful shares with low visual quality, leading to suspicion of encryption. This paper introduces the concept of visual information pixel (VIP) synchronization and error diffusion to attain a color visual cryptography encryption method that produces meaningful color shares with high visual quality. VIP synchronization retains the positions of pixels carrying visual information of original images throughout the color channels and error diffusion generates shares pleasant to human eyes. Comparisons with previous approaches show the superior performance of the new method.
     

Structure and Texture Filling-In of Missing Image Blocks in Wireless Transmission and Compression Applications (2007)

ABSTRACT
An approach for filling-in blocks of missing data in wireless image transmission is presented in this paper. When compression algorithms such as JPEG are used as part of the wireless transmission process, images are first tiled into blocks of 8 8 pixels. When such images are transmitted over fading channels, the effects of noise can destroy entire blocks of the image. Instead of using common retransmission query protocols, we aim to reconstruct the lost data using correlation between the lost block and its neighbors. If the lost block contained structure, it is reconstructed using an image inpainting algorithm, while texture synthesis is used for the textured blocks. The switch between the two schemes is done in a fully automatic fashion based on the surrounding available blocks. The performance of this method is tested for various images and combinations of lost blocks. For our implementation, we consider PGM (Portable Gray Map) images for filling in of missing image blocks. We use Java 2, The Standard Edition for implementing the algorithm, and the holes (missing blocks) are placed randomly for testing the project.
     

Secure Mask for Color Image Hiding (2007)

ABSTRACT
Hiding image in a color image is a very interesting research topic; especially using very popular software such as Microsoft Windows Paint, Internet Explorer Browser (IE) Mozilla Firefox, etc can achieve very amazing result. In this paper, we start from the select operation of IE, and introduce the mechanism how to hide a color image in a real natural image. Based on this, we generate an animation using this scheme. Using the select function of IE, we can toggle two completely different animations. We improve the hiding scheme and introduce how to embed the shares of visual cryptography into a natural color image, another share of visual cryptography works as a public key like the select operation of IE. We also introduce how to hide a visual cryptography share into a halftone image. The results are very robust and can resist print and scan tempering.
     

A Memory Learning Framework for Effective Image Retrieval (2005)

ABSTRACT
Most current content-based image retrieval systems are still incapable of providing users with their desired results. The major difficulty lies in the gap between low-level image features and high-level image semantics. To address the problem, this study reports a framework for effective image retrieval by employing a novel idea of memory learning. It forms a knowledge memory model to store the semantic information by simply accumulating user-provided interactions. A learning strategy is then applied to predict the semantic relationships among images according to the memorized knowledge. Image queries are finally performed based on a seamless combination of low-level features and learned semantics. One important advantage of our framework is its ability to efficiently annotate images and also propagate the keyword annotation from the labeled images to unlabeled images. The presented algorithm has been integrated into a practical image retrieval system. Experiments on a collection of 10 000 general-purpose images demonstrate the effectiveness of the proposed framework.
     

Application of BPCS steganography to wavelet compressed video (2004)

ABSTRACT
This paper presents a Stegnography method using lossy compressed video which provides a natural way to send a large amount of secret data. The proposed method is based on wavelet compression for video data and bit-plane complexity segmentation (BPCS) Stegnography. In wavelet based video compression methods such as 3-D set partitioning in hierarchical trees (SPIHT) algorithm and Motion- JPEG2000, wavelet coefficients in discrete wavelet transformed video are quantized into a bit-plane structure and therefore BPCS Stegnography can be applied in the wavelet domain. 3-D SPIHT-BPCS Stegnography and Motion- JPEG2000-BPCS Stegnography are presented and tested, which are the integration of 3-D SPIHT video coding and BPCS Stegnography, and that of Motion-JPEG2000 and BPCS, respectively. Experimental results show that 3-D SPIHT-BPCS is superior to Motion-JPEG2000-BPCS with regard to embedding performance.
     

Noise Reduction by Fuzzy Image Filtering (2003)

ABSTRACT
A new fuzzy filter is presented for the noise reduction of images corrupted with additive noise. The filter consists of two stages. The first stage computes a fuzzy derivative for eight different directions. The second stage uses these fuzzy derivatives to perform fuzzy smoothing by weighting the contributions of neighboring pixel values. Both stages are based on fuzzy rules which make use of membership functions. The filter can be applied iteratively to effectively reduce heavy noise. In particular, the shape of the membership functions is adapted according to the remaining noise level after each iteration, making use of the distribution of the homogeneity in the image. A statistical model for the noise distribution can be incorporated to relate the homogeneity to the adaptation scheme of the membership functions. Experimental results are obtained to show the feasibility of the proposed approach. These results are also compared to other filters by numerical measures and visual inspection.
     

A Perceptually Relevant Approach to Ringing Region Detection 2010

ABSTRACT
An efficient approach toward a no-reference ringing metric intrinsically exists of two steps: first detecting regions in an image where ringing might occur, and second quantifying the ringing annoyance in these regions. This paper presents a novel approach toward the first step: the automatic detection of regions visually impaired by ringing artifacts in compressed images. It is a no-reference approach, taking into account the specific physical structure of ringing artifacts combined with properties of the human visual system (HVS). To maintain low complexity for real-time applications, the proposed approach adopts a perceptually relevant edge detector to capture regions in the image susceptible to ringing, and a simple yet efficient model of visual masking to determine ringing visibility. The approach is validated with the results of a psycho visual experiment, and its performance is compared to existing alternatives in literature for ringing region detection. Experimental results show that our method is promising in terms of both reliability and computational efficiency
     

An Improved Lossless Image Compression Algorithm LOCO-R  2010

ABSTRACT
This paper presents a state-of-the-art implementation of lossless image compression algorithm LOCO-R, which is based on the LOCO-I (low complexity lossless compression for images) algorithm developed by weinberger, Seroussi and Sapiro, with modifications and betterment, the algorithm reduces obviously the implementation complexity. Experiments illustrate that this algorithm is better than Rice Compression typically by around 15 percent.
     

Cheating Prevention in Visual Cryptography 2007

ABSTRACT
Visual Cryptography (VC) is a method of encrypting a secret image in to n shares such that stacking a sufficient number of shares reveals the secret image. Unlike conventional cryptographic methods, VC needs no complicated computation for recovering the secret. The act of decryption is to stack shares which is the bitwise OR operation of pixels in the shares. Most of the previous research work on Visual Cryptography focuses on improving two parameters Pixel expansion and contrast. This paper considers the attacks of malicious adversaries who may deviate from the scheme in any way. There are three cheating methods that are applied on existing Visual Cryptography schemes. This paper improves one of the cheat-preventing schemes. A generic method that converts a Visual Cryptography scheme to another Visual Cryptography scheme that has the property of cheating prevention is proposed. The overhead of the conversion is near optimal in both contrast degression and pixel expansion.
     

Discriminative Learning and Recognition of Image set classes Using Canonical Correlation 2007

ABSTRACT
We address the problem of comparing sets of images for object recognition, where the sets may represent variations in an object’s appearance due to changing camera pose and lighting conditions. Canonical Correlations (also known as principal or canonical angles), which can be thought of as the angles between two d-dimensional subspaces, have recently attracted attention for image set matching. Canonical correlations offer many benefits in accuracy, efficiency, and robustness compared to the two main classical methods: parametric distribution-based and nonparametric sample-based matching of sets. Here, this is first demonstrated experimentally for reasonably sized data sets using existing methods exploiting canonical correlations. Motivated by their proven effectiveness, a novel discriminative learning method over sets is proposed for set classification. Specifically, inspired by classical Linear Discriminant Analysis (LDA), we develop a linear discriminant function that maximizes the canonical correlations of within-class sets and minimizes the canonical correlations of between-class sets. Image sets transformed by the discriminant function are then compared by the canonical correlations. Classical orthogonal subspace method (OSM) is also investigated for the similar purpose and compared with the proposed method. The proposed method is evaluated on various object recognition problems using face image sets with arbitrary motion captured under different illuminations and image sets of 500 general objects taken at different views. The method is also applied to object category recognition using ETH-80 database. The proposed method is shown to outperform the state-of-the-art methods in terms of accuracy and efficiency.
     

Conceptual Cohesion of Classes in Object Oriented Systems (2008)

ABSTRACT
Cohesion measures in Object-oriented software reflect particular interpretations, High cohesion positively impacts understanding, reuse and maintenance. This paper proposes a new measure based on analysis of the unstructured information embedded in the source code, such as comments and identifiers, we have the existing applications based on using the only the structural information from the source code, attribute references in methods to measure cohesion. The new measure named the Conceptual cohesion of classes is the mechanisms used to measure textual coherence in cognitive psychology and computational linguistics, presents the principles and the technology that stand behind the C3 measure. A large case study on three open source software systems is presented which compares the new measure with an extensive set of existing metrics and uses them to construct models that predict software faults. The case study shows that the design concepts and novel measure captures different aspects of class cohesion compared to any of the existing cohesion measures


     

NDT A Model-Driven Approach  (2008)

ABSTRACT
Web engineering is a new research line in software engineering that covers the definition of processes, techniques, and models suitable for Web environments in order to guarantee the quality of results. The research community is working in this area and, as a very recent line, they are assuming the Model-Driven paradigm to support and solve some classic problems detected in Web developments. However, there is a lack in Web requirements treatment. This paper presents a general vision of Navigational Development Techniques (NDT), which is an approach to deal with requirements in Web systems. It is based on conclusions obtained in several comparative studies and it tries to fill some gaps detected by the research community. This paper presents its scope, its most important contributions, and offers a global vision of its associated tool: NDT-Tool. Furthermore, it analyzes how Web Engineering can be applied in the enterprise environment. NDT is being applied in real projects and has been adopted by several companies as a requirements methodology. The approach offers a Web requirements solution based on a Model-Driven paradigm that follows the most accepted tendencies by Web engineering.


     

Problem Oriented Software Engineering Solving the Package Router Control Problem (2008)

ABSTRACT
Problem orientation is gaining interest as a way of approaching the development of software intensive systems, and yet, a significant example that explores its use is missing from the literature. In this paper, we present the basic elements of Problem Oriented Software Engineering (POSE), which aims at bringing both non-formal and formal aspects of software development together in a single framework. We provide an example of a detailed and systematic POSE development of a software problem: that of designing the controller for a package router. The problem is drawn from the literature, but the analysis presented here is new. The aim of the example is twofold: to illustrate the main aspects of POSE and how it supports software engineering design and to demonstrate how a nontrivial problem can be dealt with by the approach.


     

Security Requirements Engineering A Framework for Representation and Analysis (2008)

ABSTRACT
This paper presents a framework for security requirements elicitation and analysis. The framework is based on constructing a context for the system, representing security requirements as constraints, and developing satisfaction arguments for the security requirements. The system context is described using a problem-oriented notation, then is validated against the security requirements through construction of a satisfaction argument. The satisfaction argument consists of two parts: a formal argument that the system can meet its security requirements and a structured informal argument supporting the assumptions expressed in the formal argument. The construction of the satisfaction argument may fail, revealing either that the security requirement cannot be satisfied in the context or that the context does not contain sufficient information to develop the argument. In this case, designers and architects are asked to provide additional design information to resolve the problems. We evaluate the framework by applying it to a security requirements analysis within an air traffic control technology evaluation project.


     

Using the Conceptual Cohesion of Classes for Fault Prediction in Object-Oriented Systems (2008)

ABSTRACT
High cohesion is desirable property in software systems to achieve reusability and maintainability. In this project we are measures for cohesion in Object-Oriented software reflect particular interpretations of cohesion and capture different aspects of it. In existing approaches the cohesion is calculate from the structural information for example method attributes and references. In conceptual cohesion of classes, i.e. in our project we are calculating the unstructured information from the source code such as comments and identifiers. Unstructured information is embedded in the source code. To retrieve the unstructured information from the source code Latent Semantic Indexing is used. A large case study on three open source software systems is presented which compares the new measure with an extensive set of existing metrics and uses them to construct models that predict software faults. In our project we are achieving the high cohesion and we are predicting the fault in Object Oriented Systems.


     

API-Based and Information-Theoretic - Coupling based metrics for measuring the quality of a software (2007)

ABSTRACT
The main aim of this project is to introduce a new set of metrics that measure the quality of modularization of a object-oriented software system. These metrics characterize the software from a variety of perspectives such as structural, architectural and notions like similarity of purposes. Structural refers to inter-module coupling-based notions. Architectural refers to the horizontal layering of modules in large software systems. The notion of API (Application Programming Interface) is employed as the basis for the structural metrics. Some of the important support metrics include those that characterize each module on the basis of the similarity of purpose of the services offered by the module. Here coupling-based structural metrics are used that provide various measures of the function-call traffic through the APIs of the modules in relation to the overall function-call traffic. Here functional call traffic refers to the inter-modular interaction. The existing system measures the software quality using code complexity and maintainability. In existing system performance analysis takes more time as well as not more accurate. The drawbacks are eliminated by coupling based structured metrics.


     

Using the Conceptual Cohesion of Classes for Fault Prediction in Object-Oriented Systems 2007

ABSTRACT
High cohesion is desirable property in software systems to achieve reusability and maintainability. In this project we are measures for cohesion in Object-Oriented (OO) software reflect particular interpretations of cohesion and capture different aspects of it. In existing approaches the cohesion is calculate from the structural information for example method attributes and references. In conceptual cohesion of classes, i.e. in our project we are calculating the unstructured information from the source code such as comments and identifiers. Unstructured information is embedded in the source code. To retrieve the unstructured information from the source code Latent Semantic Indexing is used. A large case study on three open source software systems is presented which compares the new measure with an extensive set of existing metrics and uses them to construct models that predict software faults. In our project we are achieving the high cohesion and we are predicting the fault in Object –Oriented Systems.
     

A Parallel Approach To XML Parsing (2006)

ABSTRACT
A language for semi-structured documents, XML has emerged as the core of the web services architecture, and is playing crucial roles in messaging systems, databases, and document processing. However, the processing of XML documents has a reputation for poor performance, and a number of optimizations have been developed to address this performance problem from different perspectives, none of which have been entirely satisfactory. In this paper, we present a seemingly quixotic, but novel approach: parallel XML parsing. Parallel XML parsing leverages the growing prevalence of multi core architectures in all sectors of the computer market, and yields significant performance improvements. This paper presents our design and implementation of parallel XML parsing. Our design consists of an initial preparsing phase to determine the structure of the XML document, followed by a full, parallel parse. The results of the preparsing phase are used to help partition the XML document for data parallel processing. Our parallel parsing phase is a modification of the libxml2 XML parser, which shows that our approach applies to real-world, production quality parsers. Our empirical study shows our parallel XML parsing algorithm can improved the XML parsing performance significantly and scales well.