YouTube社交网络中基于兴趣的逐社区P2P短视频共享层次结构

Haiying Shen, Yuhua Lin, Harrison Chandler
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引用次数: 8

摘要

过去几年,youtube上的在线短视频分享出现了爆炸式增长。随着用户数量的持续增长,维持可接受的服务质量(QoS)所需的带宽也大大增加。点对点(P2P)架构在降低带宽成本方面显示出了希望,然而,以前的工作为每个视频构建一个P2P覆盖,这提供了有限的视频提供商的可用性,并且产生了很高的覆盖维护开销。为了解决这些问题,在这项工作中,我们新颖地利用了youtube现有的社交网络,用户订阅另一个用户的频道来跟踪他上传的所有视频。频道的订阅者倾向于观看该频道的视频,共同兴趣节点倾向于观看相同的视频。此外,一个频道的视频受欢迎程度也有很大差异。我们研究了真实的痕迹数据来证实这些特性。基于这些特性,我们提出了Social Tube,它将一个频道的订阅者构建成P2P覆盖层,并在更高的层次上聚集共同兴趣节点。它还集成了一个预取算法,可以预取更受欢迎的视频。广泛的跟踪驱动仿真结果和Planet Lab的真实世界实验结果验证了Social Tube在减少服务器负载和覆盖维护开销以及提高用户QoS方面的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Interest-Based Per-Community P2P Hierarchical Structure for Short Video Sharing in the YouTube Social Network
The past few years have seen an explosion in the popularity of online short-video sharing in You Tube. As the number of users continued to grow, the bandwidth required to maintain acceptable quality of service (QoS) has greatly increased. Peer-to-peer (P2P) architectures have shown promise in reducing the bandwidth costs, however, the previous works build one P2P overlay for each video, which provides limited availability of video providers and produces high overlay maintenance overhead. To handle these problems, in this work, we novelly leverage the existing social network in You Tube, where a user subscribes to another user's channel to track all his uploaded videos. The subscribers of a channel tend to watch the channel's videos and common-interest nodes tend to watch the same videos. Also, the popularity of videos in one channel varies greatly. We study real trace data to confirm these properties. Based on these properties, we propose Social Tube that builds the subscribers of one channel into a P2P overlay and also clusters common-interest nodes in a higher level. It also incorporates a prefetching algorithm that prefetches higher-popularity videos. Extensive trace-driven simulation results and Planet Lab real world experimental results verify the effectiveness of Social Tube at reducing server load and overlay maintenance overhead and at improving QoS for users.
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