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. In 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.
In recent years, overlay networks have proven a popular way of disseminating potentially large files (such as a new software product or a video) from a single server @math to a potentially large group of @math 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 @cite_15 , Slurpie @cite_24 , SplitStream @cite_32 , Bullet' @cite_22 and Avalanche @cite_8 , to name but a few. The key idea is that the file is divided into @math parts of equal size and that a given user may download any one of these (or, for network coding based systems such as Avalanche, linear combinations of these) either from the server or from a peer who has previously downloaded it. That is, the end users collaborate by forming a P2P network of peers, so they can download from one another as well as from the server. Our motivation for revisiting the broadcasting problem is the performance analysis of such systems.
@cite_22 @cite_8 @cite_32 @cite_24 @cite_15
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The widespread use of peer-to-peer (P2P) systems has made multimedia content sharing more efficient. Users in a P2P network can query and download objects based on their preference for specific types of multimedia content. However, most P2P systems only construct the overlay architecture according to physical network constraints and do not take user preferences into account. In this paper, we investigate a social-based overlay that can cluster peers that have similar preferences. To construct a semantic social-based overlay, we model a quantifiable measure of similarity between peers so that those with a higher degree of similarity can be connected by shorter paths. Hence, peers can locate objects of interest from their overlay neighbors, i.e., peers who have common interests. In addition, we propose an overlay adaptation algorithm that allows the overlay to adapt to P2P churn and preference changes in a distributed manner. We use simulations and a real database called Audioscrobbler, which tracks users' listening habits, to evaluate the proposed social-based overlay. The results show that social-based overlay adaptation enables users to locate content of interest with a higher success ratio and with less message overhead. In this paper, a simple mathematical model is presented for studying the performance of the BitTorrent (1) file sharing system. We are especially interested in the distribution of the peers with different states of the download job completedness. With the model we find that in the stable state the distribution of the download peers follows a U-shaped curve, and the parameters such as the departure rate of the seeds and the abort rate of the download peers will influence the peer distribution in different ways notably. We also analyze the file availability and the dying process of the BitTorrent file sharing system. We find that the system's stability deteriorates with the clustering of the peers, and BitTorrent's built-in "tit-for-tat" unchoking strategy could not help to preserve the integrity of the file among the download peers when the size of the community is small. An innovative peer selection strategy which enables more peers to finish the download job and prolongs the system's lifetime is proposed, in which the peers cooperate to improve the stability of the system by making a tradeoff between the current download rate and the future service availability. Finally, experimental results are presented to validate our analysis and findings. The need to distribute large files across multiple wide-area sites is becoming increasingly common, for instance, in support of scientific computing, configuring distributed systems, distributing software updates such as open source ISOs or Windows patches, or disseminating multimedia content. Recently a number of techniques have been proposed for simultaneously retrieving portions of a file from multiple remote sites with the twin goals of filling the client's pipe and overcoming any performance bottlenecks between the client and any individual server. While there are a number of interesting tradeoffs in locating appropriate download sites in the face of dynamically changing network conditions, to date there has been no systematic evaluation of the merits of different protocols. This paper explores the design space of file distribution protocols and conducts a detailed performance evaluation of a number of competing systems running in both controlled emulation environments and live across the Internet. Based on our experience with these systems under a variety of conditions, we propose, implement and evaluate Bullet' (Bullet prime), a mesh based high bandwidth data dissemination system that outperforms previous techniques under both static and dynamic conditions. We consider a network of autonomous peers forming a logically global but physically distributed search engine, where every peer has its own local collection generated by independently crawling the Web. A challenging task in such systems is to efficiently route user queries to peers that can deliver high quality results and be able to rank these returned results, thus satisfying the users' information need. However, the problem inherent with this scenario is selecting a few promising peers out of an a priori unlimited number of peers. In recent research a rather strict notion of semantic overlay networks has been established. In most approaches, peers are connected to other peers based on a rigid semantic profile by clustering them based on their contents. In contrast, our strategy follows the spirit of peer autonomy and creates semantic overlay networks based on the notion of ''peer-to-peer dating''. Peers are free to decide which connections they create and which they want to avoid based on various usefulness estimators. The proposed techniques can be easily integrated into existing systems as they require only small additional bandwidth consumption as most messages can be piggybacked onto established communication. We show how we can greatly benefit from these additional semantic relations during query routing in search engines, such as Minerva, and in the JXP algorithm, which computes the PageRank authority measure in a completely decentralized manner.