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Enhancing Traffic Locality in BitTorrent via Shared Trackers

机译:通过共享跟踪器增强BitTorrent中的流量局部

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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)应用的快速增长流量,最符说BitTorrent,对互联网服务提供商(ISP)施加前所未有的压力。因此,P2P局部人士被广泛建议减轻昂贵的ISP间流量。在本文中,我们发现即使在最受欢迎的ases(自治系统)中,很少有个体种子能够形成足够大的局部同行簇,使得最先进的地区机制用于个体种子非常低效。灵感来自同行的多种洪流行为,我们开发了一种新颖的框架,横跨多种种类的对等体的可用内容,从而有效地放大了本地共享的可能性。我们在本框架中解决了一些关键设计问题;特别是,我们讨论了对同伴迁移的检测,进一步探讨了提高同龄人激励的趋势。我们开发了一种具有共享跟踪器的智能检测机制,可实现45%的成功率而无需任何跟踪器级通信开销。我们基于追踪的仿真结果表明,我们的框架可以成功减少交叉ISP流量,并最大限度地降低对等体的下载体验的降低。

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