Inferring Network-Wide Quality in P2P Live Streaming Systems

Abstract

This paper explores how to remotely monitor network-wide quality in mesh-pull P2P live streaming systems. Peers in such systems advertise to each other buffer maps which summarize the chunks of the video stream that they currently have cached and make available for sharing. We demonstrate how buffer maps can be exploited to monitor network-wide quality. We show that the information provided in a peer's advertised buffer map correlates with that peer's viewing-continuity and startup latency. Given this correlation, we remotely harvest buffer maps from many peers and then process these buffer maps to estimate the video playback quality. We apply this methodology to a popular P2P live streaming system, namely, PPLive. To harvest buffer maps, we build a buffer-map crawler and also deploy passive sniffing nodes. We process the harvested buffer maps and present results for network-wide playback continuity, startup latency, playback lags among peers, and chunk propagation patterns. The results show that this methodology can provide reasonably accurate estimates of ongoing video playback quality throughout the network.