The subject of this thesis is searching in unstructured peer-to-peer systems. Such systems have been used for a variety of different applications, including file-sharing, content distribution and video streaming. These applications have been very popular; they contribute to a large percentage of today's Internet traffic and their users typically number in the millions. By searching, we refer to the process of locating content stored by peers. Searching in unstructured peer-to-peer systems poses a challenge because of high churn: both the topology and the content stored by peers can change quickly as peers arrive and depart, while the network formed under this churn process can be arbitrary at any point in time. As a result, a search mechanism must operate without any a priori assumptions on this dynamic topology. Ideally, a search mechanism should be scalable: as, typically, peers have limited bandwidth, the traffic generated by queries should not grow significantly as the peer population increases. Moreover, a search mechanism should also be reliable: if certain content is in the system, searching should locate it with reasonable guarantees. These two goals can be conflicting, as generating more queries increases a mechanism's reliability but decreases its scalability. Hence, a fundamental question regarding searching in unstructured systems is whether a mechanism can exhibit both properties, despite the network's dynamic and arbitrary nature. In this thesis, we show this is indeed the case, by proposing a novel mechanism that is both scalable and reliable. This is shown under a mathematical model that captures the evolution of both network and content in an unstructured system, but is also verified through simulations. To the best of our knowledge, this is the first provably scalable and reliable search mechanism for unstructured peer-to-peer systems. In addition to the above problem, we also consider a hybrid peer-to-peer system, in which the peer-to-peer network co-exists with a central server. The purpose of this hybrid architecture is to reduce the server's traffic by delegating part of it to its clients ---\emph{i.e.}, the peers: a peer wishing to retrieve certain content first propagates a query over the peer-to-peer network, and downloads the content from the server only if the query fails. This hybrid architecture can be used to partially decentralize a content distribution server, a search engine, an online encyclopedia, etc. The trade-off between scalability and reliability translates, in the hybrid case, to a trade-off between the peer and the server traffic loads. We propose a search mechanism under which both loads remain bounded as the peer population grows. This is surprising, and has an important implication: one can construct hybrid peer-to-peer systems that can handle traffic generated by a large (unbounded) peer population, even when both the server and peer bandwidth capacities are limited. Again, this is proved under a model capturing the hybrid system's dynamic nature and verified through simulations. To the best of our knowledge, our work is the first to show that hybrid systems with such properties exist.

In large-scale peer-assisted live streaming systems with hundreds of online channels, it becomes critically important to investigate the lifetime pattern of streaming sessions to have a better understanding of peer dynamics. Aiming to improve performance of the P2P streaming systems, the goal of this thesis is twofold: 1) for popular channels, we wish to identify superior peers, that contribute a higher percentage of upload capacities and stay for a longer period of time; 2) for unpopular channels, we seek to explore factors that affect the peer instability. Utilizing more than 130 GB worth of run-time traces from a large-scale real-world live streaming system, UUSee, we conduct a comprehensive and in-depth statistical analysis. Using survival analysis techniques, we discover critical factors that may influence the longevity. Based on the Cox regression models we built, we also discuss several interesting insights from our measurement results.

In large-scale peer-assisted live streaming systems with hundreds of online channels, it becomes critically important to investigate the lifetime pattern of streaming sessions to have a better understanding of peer dynamics. Aiming to improve performance of the P2P streaming systems, the goal of this thesis is twofold: 1) for popular channels, we wish to identify superior peers, that contribute a higher percentage of upload capacities and stay for a longer period of time; 2) for unpopular channels, we seek to explore factors that affect the peer instability. Utilizing more than 130 GB worth of run-time traces from a large-scale real-world live streaming system, UUSee, we conduct a comprehensive and in-depth statistical analysis. Using survival analysis techniques, we discover critical factors that may influence the longevity. Based on the Cox regression models we built, we also discuss several interesting insights from our measurement results.

The proliferation of online communities on the Internet nowadays may lead people to the conclusion that the development of custom-made communities for particular purpose is straightforward. Unfortunately, this is not the case. Although software providing basic community infrastructure is readily available, it is not enough to ensure that the online community will take off and become sustained. Most online communities suffer from the scarcity of the user participation in their initial phase. To address the problem, this thesis proposes a motivational mechanism to encourage user participation. The main idea is to introduce a set of hierarchical memberships into online communities and reward active users with better quality of services. The mechanism has been applied in a small-scale online community called Comtella and evaluated. The results showed that, although the mechanism was able to motivate users to participate more actively and make more contributions, it led to a deteriorating quality of user contributions, catalyzed information overload in the community and resulted in a decrease in user participation towards the end of the study. <p> Therefore, to regulate the quality and the quantity of user contributions and ensure a sustainable level of user participation in the online community, the proposed mechanism was improved so that it was able to adapt the rewards for particular forms of participation for individual users depending on their reputation and the current need of the community, thereby influencing their actions of contributing. The improved mechanism was also implemented and evaluated in the Comtella system. The results of evaluation showed that the mechanism can guarantee stable and active user participation and lower the level of information overload in the online community and therefore it can enhance the sustainability of the community.

Demands for multimedia content, one form of digital content, are continuously increasing at a phenomenal pace, as video features are commonly available on personal devices, such as iPod, cell phone, laptop, PDA, and Blackberry. The streaming service poses unique bandwidth and delay challenges to application designers. The size of a typical video content is usually orders of magnitude larger than that of any other type of content, resulting in high demands for bandwidth contribution from the content providers. Even more challenging, the content must be delivered to end hosts in real time to maintain smooth playback, i.e., the content must be transmitted at a satisfactory rate. In this thesis, we present our research towards a high-quality peer-to-peer live streaming system that utilizes network coding, a novel technique that permits coding at every peer, which has proven benefits in file dissemination applications. To ensure the practicality of our work, it is our imperative objective to conduct all experiments under realistic settings.

The subject of this thesis is searching in unstructured peer-to-peer systems. Such systems have been used for a variety of different applications, including file-sharing, content distribution and video streaming. These applications have been very popular; they contribute to a large percentage of today's Internet traffic and their users typically number in the millions. By searching, we refer to the process of locating content stored by peers. Searching in unstructured peer-to-peer systems poses a challenge because of high churn: both the topology and the content stored by peers can change quickly as peers arrive and depart, while the network formed under this churn process can be arbitrary at any point in time. As a result, a search mechanism must operate without any a priori assumptions on this dynamic topology. Ideally, a search mechanism should be scalable: as, typically, peers have limited bandwidth, the traffic generated by queries should not grow significantly as the peer population increases. Moreover, a search mechanism should also be reliable: if certain content is in the system, searching should locate it with reasonable guarantees. These two goals can be conflicting, as generating more queries increases a mechanism's reliability but decreases its scalability. Hence, a fundamental question regarding searching in unstructured systems is whether a mechanism can exhibit both properties, despite the network's dynamic and arbitrary nature. In this thesis, we show this is indeed the case, by proposing a novel mechanism that is both scalable and reliable. This is shown under a mathematical model that captures the evolution of both network and content in an unstructured system, but is also verified through simulations. To the best of our knowledge, this is the first provably scalable and reliable search mechanism for unstructured peer-to-peer systems. In addition to the above problem, we also consider a hybrid peer-to-peer system, in which the peer-to-peer network co-exists with a central server. The purpose of this hybrid architecture is to reduce the server's traffic by delegating part of it to its clients ---\emph{i.e.}, the peers: a peer wishing to retrieve certain content first propagates a query over the peer-to-peer network, and downloads the content from the server only if the query fails. This hybrid architecture can be used to partially decentralize a content distribution server, a search engine, an online encyclopedia, etc. The trade-off between scalability and reliability translates, in the hybrid case, to a trade-off between the peer and the server traffic loads. We propose a search mechanism under which both loads remain bounded as the peer population grows. This is surprising, and has an important implication: one can construct hybrid peer-to-peer systems that can handle traffic generated by a large (unbounded) peer population, even when both the server and peer bandwidth capacities are limited. Again, this is proved under a model capturing the hybrid system's dynamic nature and verified through simulations. To the best of our knowledge, our work is the first to show that hybrid systems with such properties exist.

This thesis work concerns about the Performance evolution of peer to peer networks, where we used different distribution technique’s of peer distribution like Weibull, Lognormal and Pareto distribution process. Then we used a network simulator to evaluate the performance of these three distribution techniques.During the last decade the Internet has expanded into a world-wide network connecting millions of hosts and users and providing services for everyone. Many emerging applications are bandwidth-intensive in their nature; the size of downloaded files including music and videos can be huge, from ten megabits to many gigabits. The efficient use of network resources is thus crucial for the survivability of the Internet. Traffic engineering (TE) covers a range of mechanisms for optimizing operational networks from the traffic perspective. The time scale in traffic engineering varies from the short-term network control to network planning over a longer time period.Here in this thesis work we considered the peer distribution technique in-order to minimise the peer arrival and service process with three different techniques, where we calculated the congestion parameters like blocking time for each peer before entering into the service process, waiting time for a peers while the other peer has been served in the service block and the delay time for each peer. Then calculated the average of each process and graphs have been plotted using Matlab to analyse the results

Trust is required in file sharing peer-to-peer (P2P) systems to achieve better cooperation among peers and reduce malicious uploads. In reputation-based P2P systems, reputation is used to build trust among peers based on their past transactions and feedbacks from other peers. In these systems, reputable peers will usually be selected to upload requested files, decreasing significantly malicious uploads in the system. This thesis surveys different reputation management systems with a focus on reputation based P2P systems. We breakdown a typical reputation system into functional components. We discuss each component and present proposed solutions from the literature. Different reputation-based systems are described and analyzed. Each proposed scheme presents a particular perspective in addressing peers’ reputation. This thesis also presents a novel trust management framework and associated schemes for partially decentralized file sharing P2P systems. We address trust according to three identified dimensions: Authentic Behavior, Credibility Behavior and Contribution Behavior. Within our trust management framework, we proposed several algorithms for reputation management. In particular, we proposed algorithms to detect malicious peers that send inauthentic files, and liar peers that send wrong feedbacks. Reputable peers need to be motivated to upload authentic files by increasing the benefits received from the system. In addition, free riders need to contribute positively to the system. These peers are consuming resources without uploading to others. To provide the right incentives for peers, we develop a novel service differentiation scheme based on peers’ contribution rather than peers’ reputation. The proposed scheme protects the system against free-riders and malicious peers and reduces the service provided to them. In this thesis, we also propose a novel recommender framework for partially decentralized file sharing P2P systems. We take advantage from the partial search process used in these systems to explore the relationships between peers. The proposed recommender system does not require any additional effort from the users since implicit rating is used. The recommender system also does not suffer from the problems that affect traditional collaborative filtering schemes like the Cold start, the Data sparseness and the Popularity effect. Over all, our unified approach to trust management and recommendations allows for better system health and increased user satisfaction.

The proliferation of online communities on the Internet nowadays may lead people to the conclusion that the development of custom-made communities for particular purpose is straightforward. Unfortunately, this is not the case. Although software providing basic community infrastructure is readily available, it is not enough to ensure that the online community will take off and become sustained. Most online communities suffer from the scarcity of the user participation in their initial phase. To address the problem, this thesis proposes a motivational mechanism to encourage user participation. The main idea is to introduce a set of hierarchical memberships into online communities and reward active users with better quality of services. The mechanism has been applied in a small-scale online community called Comtella and evaluated. The results showed that, although the mechanism was able to motivate users to participate more actively and make more contributions, it led to a deteriorating quality of user contributions, catalyzed information overload in the community and resulted in a decrease in user participation towards the end of the study. <p> Therefore, to regulate the quality and the quantity of user contributions and ensure a sustainable level of user participation in the online community, the proposed mechanism was improved so that it was able to adapt the rewards for particular forms of participation for individual users depending on their reputation and the current need of the community, thereby influencing their actions of contributing. The improved mechanism was also implemented and evaluated in the Comtella system. The results of evaluation showed that the mechanism can guarantee stable and active user participation and lower the level of information overload in the online community and therefore it can enhance the sustainability of the community.

Complex networks like the Internet, peer-to-peer systems, and emerging sensor and ad-hoc networks are large distributed decentralized communication systems arising repeatedly in today's technology. In such networks it is critical to characterize network performance as the size of the network scales. The focus of my work is to relate basic network performance metrics to structural characteristics of underlying network topologies, and to develop protocols that reinforce and exploit desired structural characteristics. For the case of the Internet at the Autonomous System level, we relate the graph theoretic notions of conductance and spectrum to network clustering and network congestion. In particular, we show how spectral analysis can identify clusters, and how the presence of clusters affects congestion. This is important for network prediction and network simulation. For the case of peer-to-peer networks we relate conductance and spectral gap to the fundamental questions of searching and topology maintenance. We propose new protocols for maintaining peer-to-peer networks with good conductance and low network overhead. We compare the performance of the traditional method of search by flooding to searching by random walks. We isolate cases of practical interest, such as clustered and dynamic network topologies, where the latter have superior performance. The improvement in the performance can be directly quantified in terms of the conductance of the underlying topology. We introduce further hybrid search schemes, of which flooding and random walks are special instances, which aim to improve the performance of searching by using locally maintained information about the network topology.