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Exploiting Locality of Interest in Online Social Networks

机译:利用在线社交网络的感兴趣的地方

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Online Social Networks (OSN) are fun, popular, and socially significant. An integral part of their success is the immense size of their global user base. To provide a consistent service to all users, Facebook, the world's largest OSN, is heavily dependent on centralized U.S. data centers, which renders service outside of the U.S. sluggish and wasteful of Internet bandwidth. In this paper, we investigate the detailed causes of these two problems and identify mitigation opportunities. Because details of Facebook's service remain proprietary, we treat the OSN as a black box and reverse engineer its operation from publicly available traces. We find that contrary to current wisdom, OSN state is amenable to partitioning and that its fine grained distribution and processing can significantly improve performance without loss in service consistency. Through simulations of reconstructed Facebook traffic over measured Internet paths, we show that user requests can be processed 79% faster and use 91% less bandwidth. We conclude that the partitioning of OSN state is an attractive scaling strategy for Facebook and other OSN services.
机译:在线社交网络(OSN)很有趣,流行,社会意义。他们成功的一个组成部分是全球用户群的巨大规模。为了向所有用户提供一致的服务,Facebook是世界上最大的OSN,严重依赖于集中式美国数据中心,该中心呈现在美国外面的服务迟钝和浪费互联网带宽。在本文中,我们调查了这两个问题的详细原因,并确定了缓解机会。由于Facebook的服务的细节仍然是专有的,因此我们将OSN视为黑匣子,并从公开的迹线逆转工程师。我们发现与目前的智慧相反,OSN状态可供分区,并且其细粒度分布和处理可以显着提高性能而不会损失服务一致性。通过仿真重建的Facebook流量通过测量的Internet路径,我们表明用户请求可以更快地处理79%并使用91%的带宽。我们得出结论,奥恩州国家的分区是Facebook和其他OSN服务的有吸引​​力的扩展策略。

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