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Minimizing File Download Time in Stochastic Peer-to-Peer Networks

机译:最大限度地减少随机点对点网络中的文件下载时间

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摘要

The peer-to-peer (P2P) file-sharing applications are becoming increasingly popular and account for more than 70% of the Internet''s bandwidth usage. Measurement studies show that a typical download of a file can take from minutes up to several hours depending on the level of network congestion or the service capacity fluctuation. In this paper, we consider two major factors that have significant impact on average download time, namely, the spatial heterogeneity of service capacities in different source peers and the temporal fluctuation in service capacity of a single source peer. We point out that the common approach of analyzing the average download time 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 and then analyze a simple, distributed algorithm to effectively remove these negative factors, thus minimizing the average download time. We show through analysis and simulations that it outperforms most of other algorithms currently used in practice under various network configurations.
机译:对等(P2P)文件共享应用程序变得越来越流行,并且占Internet带宽使用量的70%以上。测量研究表明,根据网络拥塞程度或服务容量波动,典型的文件下载可能需要几分钟到几小时才能完成。在本文中,我们考虑了对平均下载时间有重大影响的两个主要因素,即不同源对等方服务能力的空间异质性和单个源对等方服务能力的时间波动。我们指出,基于平均服务容量来分析平均下载时间的通用方法在根本上是有缺陷的。我们严格证明,空间异质性和服务容量的时间相关性都会增加P2P网络中的平均下载时间,然后分析一种简单的分布式算法来有效消除这些负面因素,从而最大程度地减少平均下载时间。通过分析和仿真,我们证明了它在各种网络配置下都优于目前在实践中使用的大多数其他算法。

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