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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Zhengye Liu Yuan Ding Yong Liu Ross, K. |
| Copyright Year | 2012 |
| Description | Author affiliation: AT&T Labs, San Ramon, USA (Zhengye Liu) || Computer Science & Engineering, Polytechnic Institute of New York University, USA (Yuan Ding; Ross, K.) || Electrical & Computer Engineering, Polytechnic Institute of New York University, USA (Yong Liu) |
| Abstract | User Generated Content (UGC) video applications, such as YouTube, are enormously popular. UGC systems can potentially reduce their distribution costs by allowing peers to store and redistribute the videos that they have seen in the past. We study peer-assisted UGC from three perspectives. First, we undertake a measurement study of the peer-assisted distribution system of Tudou (a popular UGC network in China), revealing several fundamental characteristics that models need to take into account. Second, we develop analytical models for peer-assisted distribution of UGC. Our models capture essential aspects of peer-assisted UGC systems, including system size, peer bandwidth heterogeneity, limited peer storage, and video characteristics. We apply these models to numerically study YouTube-like UGC services. And third, we develop analytical models to understand the rate at which users would install P2P client applications to make peer-assisted UGC a success. Our results provide a comprehensive study of peer-assisted UGC distribution, exposing its fundamental characteristics and limitations. |
| Starting Page | 261 |
| Ending Page | 272 |
| File Size | 237757 |
| Page Count | 12 |
| File Format | |
| ISBN | 9781467328609 |
| e-ISBN | 9781467328623 |
| e-ISBN | 9781467328616 |
| DOI | 10.1109/P2P.2012.6335807 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2012-09-03 |
| Publisher Place | Spain |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Bandwidth Servers Streaming media Optimal scheduling Monte Carlo methods YouTube Upper bound |
| Content Type | Text |
| Resource Type | Article |
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