Seed Scheduling for Peer-to-Peer Networks

The initial phase in a content distribution (file sharing) scenario is a delicate phase due to the lack of global knowledge and the dynamics of the overlay. An unwise distribution of the pieces in this phase can cause delays in reaching steady state, thus increasing file download times. We devise a scheduling algorithm at the seed (source peer with full content), based on a proportional fair approach, and we implement it on a real file sharing client [1]. In dynamic overlays, our solution improves up to 25% the average downloading time of a standard protocol ala BitTorrent.

Enabling Robust and Efficient Distributed Computation in Dynamic Peer-to-Peer Networks

Motivated by the need for designing efficient and robust fully-distributed computation in highly dynamic networks such as Peer-to-Peer (P2P) networks, we study distributed protocols for constructing and maintaining dynamic network topologies with good expansion properties. Our goal is to maintain a sparse (bounded degree) expander topology despite heavy {\em churn} (i.e., nodes joining and leaving the network continuously over time). We assume that the churn is controlled by an adversary that has complete knowledge and control of what nodes join and leave and at what time and has unlimited computational power, but is oblivious to the random choices made by the algorithm. Our main contribution is a randomized distributed protocol that guarantees with high probability the maintenance of a {\em constant} degree graph with {\em high expansion} even under {\em continuous high adversarial} churn. Our protocol can tolerate a churn rate of up to $O(n/\poly\log(n))$ per round (where $n$ is the stable network size). Our protocol is efficient, lightweight, and scalable, and it incurs only $O(\poly\log(n))$ overhead for topology maintenance: only polylogarithmic (in $n$) bits needs to be processed and sent by each node per round and any node's computation cost per round is also polylogarithmic. The given protocol is a fundamental ingredient that is needed for the design of efficient fully-distributed algorithms for solving fundamental distributed computing problems such as agreement, leader election, search, and storage in highly dynamic P2P networks and enables fast and scalable algorithms for these problems that can tolerate a large amount of churn.

Supporting ad hoc collaborations in peer-to-peer networks

Traditionally, applications and tools supporting collaborative computing have been designed only with personal computers in mind and support a limited range of computing and network platforms. These applications are therefore not well equipped to deal with network heterogeneity and, in particular, do not cope well with dynamic network topologies. Progress in this area must be made if we are to fulfil the needs of users and support the diversity, mobility, and portability that are likely to characterise group work in future. This paper describes a groupware platform called Coco that is designed to support collaboration in a heterogeneous network environment. The work demonstrates that progress in the p development of a generic supporting groupware is achievable, even in the context of heterogeneous and dynamic networks. The work demonstrates the progress made in the development of an underlying communications infrastructure, building on peer-to-peer concept and topologies to improve scalability and robustness.

PERFORMANCE EVOLUTION OF PEER TO PEER NETWORKS

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

Massive data delivery in unstructured peer-to-peer networks with network coding

With more and more multimedia applications on the Internet, such as IPTV, bandwidth becomes a vital bottleneck for the booming of large scale Internet based multimedia applications. Network coding is recently proposed to take advantage to use network bandwidth efficiently. In this paper, we focus on massive multimedia data, e.g. IPTV programs, transportation in peer-to-peer networks with network coding. By through study of networking coding, we pointed out that the prerequisites of bandwidth saving of network coding are: 1) one information source with a number of concurrent receivers, or 2) information pieces cached at intermediate nodes. We further proof that network coding can not gain bandwidth saving at immediate connections to a receiver end; As a result, we propose a novel model for IPTV data transportation in unstructured peer-to-peer networks with network coding. Our preliminary simulations show that the proposed architecture works very well.

An efficient and distributed file search in unstructured peer-to-peer networks

Peer-to-peer (P2P) networks are gaining increased attention from both the scientific community and the larger Internet user community. Data retrieval algorithms lie at the center of P2P networks, and this paper addresses the problem of efficiently searching for files in unstructured P2P systems. We propose an Improved Adaptive Probabilistic Search (IAPS) algorithm that is fully distributed and bandwidth efficient. IAPS uses ant-colony optimization and takes file types into consideration in order to search for file container nodes with a high probability of success. We have performed extensive simulations to study the performance of IAPS, and we compare it with the Random Walk and Adaptive Probabilistic Search algorithms. Our experimental results show that IAPS achieves high success rates, high response rates, and significant message reduction.

Experiences in developing a micro-payment system for peer-to-peer networks

Micro-payment systems are an important part of peer-to-peer (P2P) networks and address the "free-rider" problem in most existing content sharing systems. To address this issue, the authors have developed a new micro-payment system for content sharing in P2P networks called P2P-Netpay. This is an offline, debit based protocol that provides a secure, flexible, usable and reliable credit service. This article compares micro-payment with non-micro-payment credit systems for file sharing applications and finds that this approach liberates the "free-rider" problem. The authors analyse the heuristic evaluation performed by a set of evaluators and present directions for research aiming to improve the overall satisfaction and efficiency of the proposed model.

Evolutionary methods for self-organizing cooperation in peer-to-peer networks

The Peer-to-Peer network paradigm is drawing the attention of both final users and researchers for its features. P2P networks shift from the classic client-server approach to a high level of decentralization where there is no central control and all the nodes should be able not only to require services, but to provide them to other peers as well. While on one hand such high level of decentralization might lead to interesting properties like scalability and fault tolerance, on the other hand it implies many new problems to deal with. A key feature of many P2P systems is openness, meaning that everybody is potentially able to join a network with no need for subscription or payment systems. The combination of openness and lack of central control makes it feasible for a user to free-ride, that is to increase its own benefit by using services without allocating resources to satisfy other peers’ requests. One of the main goals when designing a P2P system is therefore to achieve cooperation between users. Given the nature of P2P systems based on simple local interactions of many peers having partial knowledge of the whole system, an interesting way to achieve desired properties on a system scale might consist in obtaining them as emergent properties of the many interactions occurring at local node level. Two methods are typically used to face the problem of cooperation in P2P networks: 1) engineering emergent properties when designing the protocol; 2) study the system as a game and apply Game Theory techniques, especially to find Nash Equilibria in the game and to reach them making the system stable against possible deviant behaviors. In this work we present an evolutionary framework to enforce cooperative behaviour in P2P networks that is alternative to both the methods mentioned above. Our approach is based on an evolutionary algorithm inspired by computational sociology and evolutionary game theory, consisting in having each peer periodically trying to copy another peer which is performing better. The proposed algorithms, called SLAC and SLACER, draw inspiration from tag systems originated in computational sociology, the main idea behind the algorithm consists in having low performance nodes copying high performance ones. The algorithm is run locally by every node and leads to an evolution of the network both from the topology and from the nodes’ strategy point of view. Initial tests with a simple Prisoners’ Dilemma application show how SLAC is able to bring the network to a state of high cooperation independently from the initial network conditions. Interesting results are obtained when studying the effect of cheating nodes on SLAC algorithm. In fact in some cases selfish nodes rationally exploiting the system for their own benefit can actually improve system performance from the cooperation formation point of view. The final step is to apply our results to more realistic scenarios. We put our efforts in studying and improving the BitTorrent protocol. BitTorrent was chosen not only for its popularity but because it has many points in common with SLAC and SLACER algorithms, ranging from the game theoretical inspiration (tit-for-tat-like mechanism) to the swarms topology. We discovered fairness, meant as ratio between uploaded and downloaded data, to be a weakness of the original BitTorrent protocol and we drew inspiration from the knowledge of cooperation formation and maintenance mechanism derived from the development and analysis of SLAC and SLACER, to improve fairness and tackle freeriding and cheating in BitTorrent. We produced an extension of BitTorrent called BitFair that has been evaluated through simulation and has shown the abilities of enforcing fairness and tackling free-riding and cheating nodes.

Music Piracy on Peer-to-Peer Networks

Content providers from the music industry argue that peer-to-peer (P2P) networks such as KaZaA, Morpheus, iMesh, or Audiogalaxy are an enormous threat to their business. They furthermore blame these networks for their recent decline in sales figures. For this reason, an empirical investigation was conducted during a period of 6 weeks on one of the most popular files-sharing systems, in order to determine the quantity and quality of pirated music songs shared. We present empirical evidence as to what extent and in which quality music songs are being shared. A number of hypotheses are outlined and were tested. We studied, among other things, the number of users online and the number of flies accessible on such networks, the free riding problem, and the duration per search request. We further tested to see if there are any differences in the accessibility of songs based on the nationality of the artist, the language of the song, and the corresponding chart position. Finally, we outline the main hurdles users may face when downloading illegal music and the probability of obtaining high quality music tracks on such peer-to-peer networks.

Clustering-based Query Routing in Cooperative Semi-structured Peer to Peer Networks

We consider the problem of resource selection in clustered Peer-to-Peer Information Retrieval (P2P IR) networks with cooperative peers. The clustered P2P IR framework presents a significant departure from general P2P IR architectures by employing clustering to ensure content coherence between resources at the resource selection layer, without disturbing document allocation. We propose that such a property could be leveraged in resource selection by adapting well-studied and popular inverted lists for centralized document retrieval. Accordingly, we propose the Inverted PeerCluster Index (IPI), an approach that adapts the inverted lists, in a straightforward manner, for resource selection in clustered P2P IR. IPI also encompasses a strikingly simple peer-specific scoring mechanism that exploits the said index for resource selection. Through an extensive empirical analysis on P2P IR testbeds, we establish that IPI competes well with the sophisticated state-of-the-art methods in virtually every parameter of interest for the resource selection task, in the context of clustered P2P IR.