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Toward Efficient Short-Video Sharing in the YouTube Social Network

机译:对YouTube社交网络中有效的短视频共享

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摘要

The past few years have seen an explosion in the popularity of online short-video sharing in YouTube. As the number of users continue 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 YouTube, where a user subscribes to another user's channel to track all his/her 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, which 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. To enhance the system performance, we further propose the demand/supply-based cache management scheme and reputation-based neighbor management scheme. Extensive trace-driven simulation results and Planet-Lab real-world experimental results verify the effectiveness of SocialTube at reducing server load and overlay maintenance overhead and at improving QoS for users.
机译:过去几年已经看到了YouTube在线短信共享的普及爆发。随着用户数量继续增长,保持可接受的服务质量(QoS)所需的带宽大大增加。点对点(P2P)架构在降低带宽成本时显示了承诺;但是,上一个工程为每个视频构建一个P2P叠加层,它为视频提供商提供有限的可用性,并在这项工作中处理这些问题的高叠加维护,以处理这些问题,我们新建了USTube中的现有社交网络,其中用户订阅到另一个用户的频道,以跟踪他/她上传的所有视频。频道的订户倾向于观看频道的视频,共同利息节点倾向于观看相同的视频。此外,一个频道中视频的普及变化大大变化。我们研究实际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,该社交管将一个通道的用户构建到P2P覆盖层中,并且还在更高级别中群集共同兴趣节点。它还包含预取高级普及视频的预取算法。为提高系统性能,我们进一步提出了基于需求/供应的高速缓存管理方案和基于信誉的邻居管理方案。广泛的追踪仿真结果和行星实验室现实世界实验结果验证了SocialTube在减少服务器负载和覆盖维护开销时的有效性以及改善用户的QoS。

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