1,058 research outputs found
Analyzing Peer Selection Policies for BitTorrent Multimedia On-Demand Streaming Systems in Internet
The adaptation of the BitTorrent protocol to multimedia on-demand streaming
systems essentially lies on the modification of its two core algorithms, namely
the piece and the peer selection policies, respectively. Much more attention
has though been given to the piece selection policy. Within this context, this
article proposes three novel peer selection policies for the design of
BitTorrent-like protocols targeted at that type of systems: Select Balanced
Neighbour Policy (SBNP), Select Regular Neighbour Policy (SRNP), and Select
Optimistic Neighbour Policy (SONP). These proposals are validated through a
competitive analysis based on simulations which encompass a variety of
multimedia scenarios, defined in function of important characterization
parameters such as content type, content size, and client interactivity
profile. Service time, number of clients served and efficiency retrieving
coefficient are the performance metrics assessed in the analysis. The final
results mainly show that the novel proposals constitute scalable solutions that
may be considered for real project designs. Lastly, future work is included in
the conclusion of this paper.Comment: 19 PAGE
Clustering and Sharing Incentives in BitTorrent Systems
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
CLOSER: A Collaborative Locality-aware Overlay SERvice
Current Peer-to-Peer (P2P) file sharing systems make use of a considerable percentage of Internet Service Providers (ISPs) bandwidth. This paper presents the Collaborative Locality-aware Overlay SERvice (CLOSER), an architecture that aims at lessening the usage of expensive international links by exploiting traffic locality (i.e., a resource is downloaded from the inside of the ISP whenever possible). The paper proves the effectiveness of CLOSER by analysis and simulation, also comparing this architecture with existing solutions for traffic locality in P2P systems. While savings on international links can be attractive for ISPs, it is necessary to offer some features that can be of interest for users to favor a wide adoption of the application. For this reason, CLOSER also introduces a privacy module that may arouse the users' interest and encourage them to switch to the new architectur
The performance and locality tradeoff in BitTorrent-like P2P file-sharing systems
The recent surge of large-scale peer-to-peer (P2P) applications has brought huge amounts of P2P traffic, which significantly changes the Internet traffic pattern and increases the traffic-relay cost at the Internet Service Providers (ISPs). To alleviate the stress on networks, localized peer selection has been proposed that advocates neighbor selection within the same network (AS or ISP) to reduce the cross-ISP traffic. Nevertheless, localized peer selection may potentially lead to the downgrade of downloading speed at the peers, rendering a non-negligible tradeoff between the downloading performance and traffic localization in the P2P system. Aiming at effective peer selection strategies that achieve any desired Pareto optimum in face of the tradeoff, in this paper, we characterize the performance and locality tradeoff as a multi-objective b-matching optimization problem. In particular, we first present a generic maximum weight b-matching model that characterizes the tit-for-tat in BitTorrent-like peer selection. We then introduce multiple optimization objectives into the model, which effectively characterize the performance and locality tradeoff using simultaneous objectives to optimize. We also design fully distributed peer selection algorithms that can effectively achieve any desired Pareto optimum of the global multi-objective optimization, that represents a desired tradeoff point between performance and locality in the entire system. Our models and algorithms are supported by rigorous analysis and extensive simulations. ©2010 IEEE.published_or_final_versionThe IEEE International Conference on Communications (ICC 2010), Cape Town, South Africa, 23-27 May 2010. In Proceedings of the IEEE International Conference on Communications, 2010, p. 1-
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