| Summary: | In large-scale peer-assisted live streaming systems with hundreds of online channels, it becomes critically important to investigate the lifetime pattern of streaming sessions to have a better understanding of peer dynamics. Aiming to improve performance of the P2P streaming systems, the goal of this thesis is twofold: 1) for popular channels, we wish to identify superior peers, that contribute a higher percentage of upload capacities and stay for a longer period of time; 2) for unpopular channels, we seek to explore factors that affect the peer instability. Utilizing more than 130 GB worth of run-time traces from a large-scale real-world live streaming system, UUSee, we conduct a comprehensive and in-depth statistical analysis. Using survival analysis techniques, we discover critical factors that may influence the longevity. Based on the Cox regression models we built, we also discuss several interesting insights from our measurement results.
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