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

机译:最小化随机对等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:点对点(P2P)文件共享应用程序越来越受欢迎,占互联网的带宽使用量的70%以上。测量研究表明,文件的典型下载可能需要几小时的时间,具体取决于网络拥塞的水平或服务能力波动。在本文中,我们考虑了对平均下载时间产生重大影响的两个主要因素,即不同源对等体的服务能力的空间异质性以及单个源对等体的服务能力中的时间波动。我们指出,分析基于平均服务能力的平均下载时间的常见方法从根本上缺陷。我们严格证明,在服务能力中的空间异质性和时间相关性增加了P2P网络中的平均下载时间,然后分析了一个简单的分布式算法,以有效地消除这些负因素,从而最小化平均下载时间。我们通过分析和模拟显示,它优于各种网络配置中目前在实践中使用的大多数其他算法。

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