Measurement-based optimization techniques for bandwidth-demanding peer-to-peer systems

Measurement-based optimization is one important strategy to improve the performance of bandwidth-demanding peer-to-peer systems. However, to date, we have little quantitative knowledge of how well basic lightweight measurement-based techniques such as RTT probing, 10KB TCP probing, and bottleneck bandwidth probing may work in practice in the peer-to-peer environment. By conducting trace-based analyses, we find that the basic techniques can help achieve 40 to 50% optimal performance. To deepen our understanding, we analyze some of the intrinsic properties of these techniques. Our analyses reveal the inherent difficulty of the peer selection problem due to the extreme heterogeneity in the peer-to-peer environment, and that the basic techniques are limited because their primary strength lies in eliminating the low-performance peers rather than reliably identifying the best-performing one. However, our analyses also reveal two key insights that can potentially be exploited by applications. First, for adaptive applications that can continuously change communication peers, the basic techniques are highly effective in guiding the adaption process. In our experiments, typically an 80% optimal peer can be found by trying less than 5 candidates. Secondly, we find that the basic techniques are highly complementary and can potentially be combined to better identify a high-performance peer, thus even applications that cannot adapt may benefit. Using media file sharing and overlay multicast streaming as case studies, we have systematically experimented with several simple combined peer selection techniques. Our results show that for the nonadaptive media file sharing application, a simple combined technique can boost performance to 60% optimal. In contrast, for the continuously adaptive overlay multicast application, we find that a basic technique with even low-fidelity network information is sufficient to ensure good performance. We believe our findings will help guide the future designs of high-performance peer-to-peer systems.