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Enhancing Traffic Locality in BitTorrent via Shared Trackers

机译:通过共享跟踪器提高BitTorrent的流量本地性

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The fast-growing traffic of peer-to-peer (P2P) applications, most notably BitTorrent, is putting unprecedented pressure to Internet Service Providers (ISPs). P2P locality has therefore been widely suggested to mitigate the costly inter-ISP traffic. In this paper, we find that even in the most popular ASes (Autonomous Systems), very few individual torrents are able to form large enough local clusters of peers, making state-of-the-art locality mechanisms for individual torrents quite inefficient. Inspired by peers' multiple torrent behavior, we develop a novel framework that traces and recovers the available contents at peers across multiple torrents, and thus effectively amplifies the possibilities of local sharing. We address some key design issues in this framework; in particular, we discuss the detection of peer migration and further explore the trends of improving peers' incentive. We develop a smart detection mechanism with shared trackers, which achieves 45% success rate without any tracker-level communication overhead. Our trace-based simulation results indicate that our framework can successfully reduce the cross-ISP traffic and minimize the possible degradation of peers' downloading experiences.
机译:对等(P2P)应用程序(尤其是BitTorrent)的快速增长给Internet服务提供商(ISP)带来了前所未有的压力。因此,广泛建议使用P2P本地地址来减轻昂贵的ISP间流量。在本文中,我们发现即使在最受欢迎的自治系统(自治系统)中,也很少有单个洪流能够形成足够大的本地对等集群,这使得针对各个洪流的最新本地化机制效率非常低下。受同伴的多次洪流行为启发,我们开发了一个新颖的框架,该框架可以跟踪和恢复同伴之间的多个洪流中的可用内容,从而有效地扩大了本地共享的可能性。我们解决了该框架中的一些关键设计问题。特别是,我们讨论了对同伴迁移的检测,并进一步探讨了改善同伴激励的趋势。我们开发了具有共享跟踪器的智能检测机制,该机制可实现45%的成功率,而无需任何跟踪器级别的通信开销。我们基于跟踪的仿真结果表明,我们的框架可以成功减少跨ISP的流量,并最大程度地降低对等方下载体验的降低。

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