On the Performance of Peer Selection Strategies in Stochastic Peer-to-Peer Networks
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Date
2009-05-08
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Abstract
Peer-to-peer (P2P) file-sharing applications are becoming increasingly popular and
account for a large portion of the Internet's bandwidth usage. Measurement studies show
that a typical download session lasts from hours up to several days depending on the level of
network congestion or the service capacity fluctuation. In this thesis, we first consider two
major factors that have significant impact on the average download time, namely, the spatial
heterogeneity of service capacities in different source peers and the temporal fluctuation in
service capacity of a given single source peer. We point out that the common approach of
analyzing the average download time, or more generally the performance of peer to peer
networks based on average service capacity is fundamentally flawed. We rigorously prove
that both spatial heterogeneity and temporal correlations in service capacity increase the
average download time in P2P networks.
We then analyze the impact of the interaction and resource competition between
peers on the file download performance under stochastic, heterogeneous, unstructured P2P
settings. We introduce the notion of system utilization tailored to a P2P network so as to
capture the characteristics of the average download time in a P2P network with multiple
competing downloading peers. We then derive an achievable lower bound on the average
download time and propose a distributed algorithm with which peers can achieve this minimum
average download time, thereby bypassing the curse of spatial heterogeneity and temporal
stochastic fluctuation. Our algorithm relies on constantly changing connected source
peers and selecting source peers probabilistically. The performance of different peer selection
algorithms is compared under NS-2 simulations. Our results also provide theoretical
explanation to the inconsistency of performance improvement by using parallel connections
(parallel connection sometimes does not outperform single connection) observed in some
measurement studies.
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Peer-to-peer, Performance Analysis
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Degree
PhD
Discipline
Electrical Engineering
