315 research outputs found

    Clustering and Sharing Incentives in BitTorrent Systems

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    Peer-to-peer protocols play an increasingly instrumental role in Internet content distribution. Consequently, it is important to gain a full understanding of how these protocols behave in practice and how their parameters impact overall performance. We present the first experimental investigation of the peer selection strategy of the popular BitTorrent protocol in an instrumented private torrent. By observing the decisions of more than 40 nodes, we validate three BitTorrent properties that, though widely believed to hold, have not been demonstrated experimentally. These include the clustering of similar-bandwidth peers, the effectiveness of BitTorrent's sharing incentives, and the peers' high average upload utilization. In addition, our results show that BitTorrent's new choking algorithm in seed state provides uniform service to all peers, and that an underprovisioned initial seed leads to the absence of peer clustering and less effective sharing incentives. Based on our observations, we provide guidelines for seed provisioning by content providers, and discuss a tracker protocol extension that addresses an identified limitation of the protocol

    Graffiti Networks: A Subversive, Internet-Scale File Sharing Model

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    The proliferation of peer-to-peer (P2P) file sharing protocols is due to their efficient and scalable methods for data dissemination to numerous users. But many of these networks have no provisions to provide users with long term access to files after the initial interest has diminished, nor are they able to guarantee protection for users from malicious clients that wish to implicate them in incriminating activities. As such, users may turn to supplementary measures for storing and transferring data in P2P systems. We present a new file sharing paradigm, called a Graffiti Network, which allows peers to harness the potentially unlimited storage of the Internet as a third-party intermediary. Our key contributions in this paper are (1) an overview of a distributed system based on this new threat model and (2) a measurement of its viability through a one-year deployment study using a popular web-publishing platform. The results of this experiment motivate a discussion about the challenges of mitigating this type of file sharing in a hostile network environment and how web site operators can protect their resources

    Towards the Coevolution of Incentives in BitTorrent

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    BitTorrent is a peer-to-peer file sharing system that is open to variant behavior at the peer level through modification of the client software. A number of different variants have been released and proposed. Some are successful and become widely used whereas others remain in a small minority or are not used at all. In previous work we explored the performance of a large set of client variants over a number of dimensions by applying Axelrod’s round-robin pairwise tournament approach. However, this approach does not capture the dynamics of client change over time within pairwise tournaments. In this work we extend the tournament approach to include a limited evolutionary step, within the pairwise tournaments, in which peers copy their opponents strategy (client variant) if it outperforms their own and also spontaneously change to the opponents strategy with a low mutation probability. We apply a number of different evolutionary algorithms and compare them with the previous non-evolutionary tournament results. We find that in most cases cooperative (sharing) strategies outperformed free riding strategies. These results are comparable to those previously obtained using the round-robin approach without evolution. We selected this limited form of evolution as a step towards understanding the full coevolutionary dynamics that would result from evolution between a large space of client variants in a shared population rather than just pairs of variants. We conclude with a discussion on how such future work might proceed. © 2015, Budapest Tech Polytechnical Institution. All rights reserved

    Understanding the Properties of the BitTorrent Overlay

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    In this paper, we conduct extensive simulations to understand the properties of the overlay generated by BitTorrent. We start by analyzing how the overlay properties impact the efficiency of BitTorrent. We focus on the average peer set size (i.e., average number of neighbors), the time for a peer to reach its maximum peer set size, and the diameter of the overlay. In particular, we show that the later a peer arrives in a torrent, the longer it takes to reach its maximum peer set size. Then, we evaluate the impact of the maximum peer set size, the maximum number of outgoing connections per peer, and the number of NATed peers on the overlay properties. We show that BitTorrent generates a robust overlay, but that this overlay is not a random graph. In particular, the connectivity of a peer to its neighbors depends on its arriving order in the torrent. We also show that a large number of NATed peers significantly compromise the robustness of the overlay to attacks. Finally, we evaluate the impact of peer exchange on the overlay properties, and we show that it generates a chain-like overlay with a large diameter, which will adversely impact the efficiency of large torrents

    An Analysis of incentives mechanisms and evaluation on BitTorrent

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    Since the first peer-to-peer communities appeared, their number of users has increased considerably owing to the benefits they offer compared to their alternative architectures in the sharing and distribution of multimedia content. However, due to its distributed nature, they can suffer an important problem of misuse: free-riding. Free-riding consists on users consuming resources without contributing to the system. Such behaviour not only is not fair for the rest of the users, but also threatens the success of this type of nets. With the motivation to avoid free-riding, the mechanisms of incentives were born. They provide the system with a method to motivate the nodes and make them share their resources with the other users. In one word, they provide the net with the needed fairness to achieve a good performance for all users. This thesis is organised in two main parts. In the first part there is a comprehensive study of the state of the art regarding the incentive mechanisms, resulting in a classification depending on the characteristics of the studied algorithms. That study provides the reader with a first sight of the strengths and weaknesses of each algorithm. In the second part there is a test scenario based in the virtualization of machines that was useful to evaluate empirically some of the studied algorithms. Finally, a series of experiments were carried out in order to compare some characteristics of these algorithms and thus verify or deny the conclusions resulted in the study of the state of the art

    A new analytical framework for studying protocol diversity in P2P networks

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    Thanks to years of research and development, current peer-to-peer (P2P) networks are anything but a homogeneous system from a protocol perspective. Specifically, even for the same P2P system (e.g., BitTorrent), a large number of protocol variants have been designed based on game theoretic considerations with the objective to gain performance advantages. We envision that such variants could be deployed by selfish participants and interact with the original prescribed protocol as well as among them. Consequently, a meta-strategic situation - judiciously selection of different protocol variants - will emerge. In this work, we propose a general framework, Migration, based on evolutionary game theory to study the coevolution of peers for selfish protocol selection, and, most importantly, its impact on system performance. We apply Migration to P2P systems and draw on extensive simulations to characterize the dynamics of selfish protocol selection. The revealed evolution patterns shed light on both theoretical study and practical system design. © 2013 IEEE.published_or_final_versio
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