Toward Efficient Short-Video Sharing in the YouTube Social Network

Author:

Shen Haiying1,Chandler Harrison2,Wang Haoyu1

Affiliation:

1. University of Virginia, Charlottesville, VA

2. University of Michigan, Ann Arbor, MI

Abstract

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 SocialTube, 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 PlanetLab real-world experimental results verify the effectiveness of SocialTube at reducing server load and overlay maintenance overhead and at improving QoS for users.

Funder

Microsoft Research Faculty Fellowship

U.S. NSF

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Networks and Communications

Reference74 articles.

1. PeerSim: A Peer-to-Peer Simulator. 2016. PeerSim P2P Simulator. Retrieved from http://peersim.sourceforge.net/. PeerSim: A Peer-to-Peer Simulator. 2016. PeerSim P2P Simulator. Retrieved from http://peersim.sourceforge.net/.

2. PPLive. 2016. PP Video. Retrieved from http://www.pplive.com. PPLive. 2016. PP Video. Retrieved from http://www.pplive.com.

3. PPStream. 2016. PPS Video. Retrieved from http://www.ppstream.com. PPStream. 2016. PPS Video. Retrieved from http://www.ppstream.com.

4. UUSee. 2016. UUSee Website. Retrieved from http://www.uusee.com. UUSee. 2016. UUSee Website. Retrieved from http://www.uusee.com.

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