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Tweeting Videos: Coordinate Live Streaming and Storage Sharing

机译:推视频:协调实时流和存储共享

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摘要

User generated video sharing (e.g., YouTube) and social-networked micro-blogging (e.g., Twitter) are among the most popular Internet applications in the Web 2.0 era. It is known that these two applications are now tightly coupled, with many new videos being tweeted among Twitter users. Unfortunately, video sharing sites are facing critical server bottlenecks and the surges created by Twitter followers would make the situation even worse. To better understand the challenges and opportunities therein, we have conducted an online user survey on their personal preference and social interest of Internet video sharing. Our data analysis reveals an interesting coexistence of live streaming and storage sharing, and that the users are generally more interested in watching their friend's videos. It further suggests that the users are willing to share their resources to assist others with close relations, implying node collaboration is a rationale choice in this context.rnIn this paper, we present COOLS (Coordinated Live Streaming and Storage Sharing), an initial attempt toward efficient peer-to-peer tweeting of user-generated videos. Through a novel ID code design that embeds nodes' locations in an overlay, COOLS leverages stable storage users and yet inherently prioritizes living streaming flows. Preliminary evaluation results show that, as compared to other state-of-the-art solutions, COOLS successfully takes advantage of the coexistence of live streaming and storage sharing, providing better scalability, robustness, and streaming quality.
机译:用户生成的视频共享(例如YouTube)和社交网络微博(例如Twitter)是Web 2.0时代最流行的Internet应用程序之一。众所周知,这两个应用程序现在紧密相连,Twitter用户之间发布了许多新视频。不幸的是,视频共享站点面临着关键的服务器瓶颈,Twitter追随者造成的激增将使情况更加恶化。为了更好地了解其中的挑战和机遇,我们针对他们对互联网视频共享的个人喜好和社会兴趣进行了在线用户调查。我们的数据分析显示了实时流媒体和存储共享的有趣共存,并且用户通常对观看朋友的视频更感兴趣。这进一步表明,用户愿意共享他们的资源以帮助与亲密关系的其他人,这意味着在这种情况下节点协作是一个合理的选择。在本文中,我们提出了COOLS(协作式实时流和存储共享),这是对用户生成的视频的高效对等推文。通过新颖的ID代码设计,将节点的位置嵌入覆盖中,COOLS可以利用稳定的存储用户,并从本质上优先考虑实时流。初步评估结果表明,与其他最新解决方案相比,COOLS成功地利用了实时流和存储共享的共存优势,从而提供了更好的可伸缩性,鲁棒性和流质量。

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