Optimal Peer-to-Peer Technique for Massive Content Distribution

Xiaoying Zheng, Chunglae Cho, Ye Xia
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引用次数: 28

Abstract

A distinct trend has emerged that the Internet is used to transport data on a more and more massive scale. Capacity shortage in the backbone networks has become a genuine possibility, which will be more serious with fiber-based access. The problem addressed in this paper is how to conduct massive content distribution efficiently in the future network environment where the capacity limitation can equally be at the core or the edge. We propose a novel peer-to-peer technique as a main content transport mechanism to achieve efficient network resource utilization. The technique uses multiple trees for distributing different file pieces, which at the heart is a version of swarming. In this paper, we formulate an optimization problem for determining an optimal set of distribution trees as well as the rate of distribution on each tree under bandwidth limitation at arbitrary places in the network. The optimal solution can be found by a distributed algorithm. The results of the paper not only provide stand-alone solutions to the massive content distribution problem, but should also help the understanding of existing distribution techniques such as BitTorrent or FastReplica.
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海量内容分发的最佳点对点技术
一个明显的趋势已经出现,互联网被用来传输越来越大规模的数据。骨干网容量不足已成为现实,光纤接入将使这一问题更加严重。本文研究的问题是如何在未来的网络环境中高效地进行海量内容分发,在这种网络环境中,容量限制可以在核心或边缘同时存在。我们提出了一种新的点对点技术作为主要的内容传输机制,以实现有效的网络资源利用。该技术使用多个树来分发不同的文件片段,其核心是蜂群的一个版本。本文提出了在网络中任意位置的带宽限制下,确定最优分布树集以及每棵树上的分布率的优化问题。通过分布式算法可以找到最优解。本文的结果不仅为海量内容分发问题提供了独立的解决方案,而且应该有助于理解现有的分发技术,如BitTorrent或FastReplica。
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