Modeling, Analysis, and Implementation of Universal Acceleration Platform Across Online Video Sharing Sites

Published in IEEE TSC, 2016

Recommended citation: Ke Xu, Tong Li*, Haiyang Wang, Haitao Li, Wei Zhu, Jiangchuan Liu and Song Lin. "Modeling, Analysis, and Implementation of Universal Acceleration Platform Across Online Video Sharing Sites." IEEE Transactions on Services Computing (TSC), vol.11, no.3, pp. 534-548, 2016. (*Corresponding author)

User-generated video sharing service has attracted a vast number of users over the Internet. The most successful sites, such as YouTube and Youku, now enjoy millions of videos being watched every day. Yet, given limited network and server resources, the user experience of existing video sharing sites (VSSes) is still far from being satisfactory. To mitigate such a problem, peer-to-peer (P2P) based video accelerators have been widely suggested to enhance the video delivery on VSSes. In this paper, we find that the interference of multiple accelerators will lead to a severe bottleneck across the VSSes. Our model analysis shows that a universal video accelerator can naturally achieve better performance with lower deployment cost. Based on this observation, we further present the detailed design of Peer-to-Peer Video Accelerator (PPVA), a real-world system for universal and transparent P2P accelerating. Such a system has already attracted over 180 million users, with 48 million video transactions every day. We carefully examine the PPVA performance from extensive measurements. Our trace analysis indicates that it can significantly reduce server bandwidth cost and accelerate the video download speed by 80 percent.

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