Joserlin

Abstract

A peer-to-peer non-linear media streaming system needs to schedule both on-demand and prefetch requests carefully so as to reduce the server load and ensure good user experience. In this work, we propose, Joserlin, a joint request and service scheduling solution that not only alleviates request contentions (requests compete for limited service capacity), but also schedules the prefetch requests by considering their contributions to potential reduction of server load. In particular, we propose a novel request binning algorithm to prevent self-contention among on-demand requests issued from the same peer. A service and rejection policy is devised to resolve contention among on-demand requests issued from different neighbors. More importantly, Joserlin employs a gain function to prioritize prefetch requests at both requesters and responders, and a prefetch request issuing algorithm to fully utilize available upload bandwidth. Evaluation with traces collected from a popular networked virtual environment shows that Joserlin leads to 20%~60% reduction in server load.