Peer-to-peer

Summary

Peer-to-peer (P2P) computing or networking is a distributed application architecture that partitions tasks or workloads between peers. Peers are equally privileged, equipotent participants in the network. This forms a peer-to-peer network of nodes. Peers make a portion of their resources, such as processing power, disk storage or network bandwidth, directly available to other network participants, without the need for central coordination by servers or stable hosts. Peers are both suppliers and consumers of resources, in contrast to the traditional client–server model in which the consumption and supply of resources are divided. While P2P systems had previously been used in many application domains, the architecture was popularized by the file sharing system Napster, originally released in 1999. The concept has inspired new structures and philosophies in many areas of human interaction. In such social contexts, peer-to-peer as a meme refers to the egalitarian social networking tha

Official source

https://en.wikipedia.org/wiki/Peer-to-peer

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Standard general-purpose Web retrieval relies on centralized search engines that do not realistically scale when applied to the exponentially growing number of documents available on the Web. By taking advantage of the resource sharing principle, Peer-to-Peer (P2P) techniques represent a promising architectural alternative for building decentralized Web search engines offering true Web-size scalability, provided that enough peers are available. However, in all such P2P approaches proposed so far, excessive network bandwidth consumption during retrieval, caused by the necessary transmission of possibly very long posting lists, was identified as the major bottleneck for implementing truly scalable P2P full-text Web retrieval. The main objective of the present research is thus to find a decentralized indexing/retrieval strategy that fully exploits the distributed computation possibilities provided by P2P networks, but keeps the required network bandwidth consumption scalable, while guaranteeing an acceptable retrieval quality. To address this problem we introduce a novel indexing/retrieval model based on Highly Discriminative Keys (HDKs), which correspond to carefully selected indexing terms and term sets associated with posting lists truncated to the top-k most relevant documents with respect to the associated key. Using HDKs for indexing thus increases the number of indexing features but, at the same time, strictly limits the size of the associated posting lists. When combined with an adequate retrieval model, this leads to strongly reduced network traffic. More precisely, our experimental results show that HDK-based indexing and retrieval lead to storage and bandwidth requirements that remain manageable with respect to the growth of document collection while preserving a fully acceptable retrieval quality.

EPFL2007

Peer-to-peer (P2P) overlay networks such as BitTorrent and Avalanche are increasingly used for disseminating potentially large files from a server to many end users via the Internet. The key idea is to divide the file into many equally-sized parts and then let users download each part (or, for network coding based systems such as Avalanche, linear combinations of the parts) either from the server or from another user who has already downloaded it. However, their performance evaluation has typically been limited to comparing one system relative to another and typically been realized by means of simulation and measurements. By contrast, we provide an analytic performance analysis that is based on a new uplink-sharing version of the well-known broadcasting problem. Assuming equal upload capacities, we show that the minimal time to disseminate the file is the same as for the simultaneous send/receive version of the broadcasting problem. For general upload capacities, we provide a mixed integer linear program (MILP) solution and a complementary fluid limit solution. We thus provide a lower bound which can be used as a performance benchmark for any P2P file dissemination system. We also investigate the performance of a decentralized strategy, providing evidence that the performance of necessarily decentralized P2P file dissemination systems should be close to this bound and therefore that it is useful in practice.

2007

In recent years, overlay networks have proven an effective way of disseminating a file from a single source to a group of end users via the Internet. A number of algorithms and protocols have been suggested, implemented and studied. In particular, much attention has been given to peer-to-peer (P2P) systems such as BitTorrent, Slurpie, SplitStream and Bullet. The key idea is that the file is divided into M parts of equal size and that a given user may download any one of these either from the server or from a peer who has previously downloaded it. More recently, a scheme based on network coding has been suggested. Here, users download linear combinations of file parts rather than individual file parts. Performance evaluation of such systems has typically been limited to comparing one system relative to another. Our results give the minimal time required to fully disseminate a file of M parts from a server to N end users. In the scheduling literature this completion time is referred to as makespan. We thus provide a lower bound which can be used as a performance benchmark for any P2P file dissemination system.

2006