I tube, you tube, everybody tubes: analyzing the world's largest user generated content video system
Proceedings of the 7th ACM SIGCOMM conference on Internet measurement
Youtube traffic characterization: a view from the edge
Proceedings of the 7th ACM SIGCOMM conference on Internet measurement
Measurement and analysis of online social networks
Proceedings of the 7th ACM SIGCOMM conference on Internet measurement
Chunkyspread: Heterogeneous Unstructured Tree-Based Peer-to-Peer Multicast
ICNP '06 Proceedings of the Proceedings of the 2006 IEEE International Conference on Network Protocols
Challenges, design and analysis of a large-scale p2p-vod system
Proceedings of the ACM SIGCOMM 2008 conference on Data communication
Characterizing user behavior in online social networks
Proceedings of the 9th ACM SIGCOMM conference on Internet measurement conference
Unveiling the patterns of video tweeting: a sina weibo-based measurement study
PAM'13 Proceedings of the 14th international conference on Passive and Active Measurement
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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. In 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.