Congestion Control in Distributed Media Streaming

Distributed media streaming, which uses multiple senders to collaboratively and simultaneously stream media content to a receiver, poses new challenges in congestion control. Such approach establishes multiple flows within a session. Since conventional congestion control only aims to make each of these flows TCP-friendly, selfish users can increase the number of flows to grab a larger share of the bandwidth, introducing more congestion and degrading the overall network performance. To address this issue, we propose the idea of task-level TCP-friendliness, which enforces TCP-friendliness upon a set of flows belonging to a task instead of upon individual flow. We design DMSCC, a congestion control scheme, to achieve task-level TCP-friendliness in distributed media streaming. By observing shared congestion, DMSCC identifies the set of flows experiencing congestion and dynamically adjusts those flows such that their combined throughput is TCP-friendly. To achieve this goal, DMSCC addresses two issues: (i) given a beta (beta < 1), how to control a flow using AIMD such that it consumes beta-times the throughput of a TCP flow, and (ii) how to identify the set of flows that share a bottleneck. In our simulations, DMSCC can effectively regulate the throughput of flows on every bottleneck, resulting in a TCP-friendly combined throughput.