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An Interest-Based Per-Community P2P Hierarchical Structure for Short Video Sharing in the YouTube Social Network

机译:YouTube社交网络中基于兴趣的按社区P2P分层结构,用于短视频共享

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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.
机译:在过去的几年中,You Tube中在线短视频共享的流行呈爆炸式增长。随着用户数量的持续增长,维持可接受的服务质量(QoS)所需的带宽已大大增加。对等(P2P)架构已显示出降低带宽成本的希望,但是,先前的工作为每个视频构建一个P2P覆盖,这限制了视频提供者的可用性,并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You Tube中现有的社交网络,用户在该社交网络上订阅另一个用户的频道以跟踪其所有上传的视频。频道的订阅者倾向于观看该频道的视频,而共同兴趣节点则倾向于观看相同的视频。同样,一个频道中视频的受欢迎程度也相差很大。我们研究真实的跟踪数据以确认这些属性。基于这些属性,我们提出了社交管,该社交管将一个频道的订户构建到P2P覆盖中,并在更高级别上聚集共同兴趣节点。它还集成了预取算法,该算法可预取人气较高的视频。大量跟踪驱动的仿真结果和Planet Lab的真实世界的实验结果验证了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。

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