In order to provide scalable live streaming service, a content provider often deploys an overlay cloud consisting of distributed servers which collaboratively exchange streams with each other. We consider an overlay consisting of multiple live channels originating from multiple sources. Server bandwidth and end-to-end network bandwidth are shared among these channels. The stream of each channel is divided into multiple substreams of a certain bitrate, each of which is pushed via a tree to the servers that subscribe to the channel. The critical and challenging issue is then how to optimize the topology of the substream trees so as to minimize the maximum channel delay ( defined as the delay from the source to the subscribing servers).

There has been little work on the optimizati...[ Read more ]

In order to provide scalable live streaming service, a content provider often deploys an overlay cloud consisting of distributed servers which collaboratively exchange streams with each other. We consider an overlay consisting of multiple live channels originating from multiple sources. Server bandwidth and end-to-end network bandwidth are shared among these channels. The stream of each channel is divided into multiple substreams of a certain bitrate, each of which is pushed via a tree to the servers that subscribe to the channel. The critical and challenging issue is then how to optimize the topology of the substream trees so as to minimize the maximum channel delay ( defined as the delay from the source to the subscribing servers).

There has been little work on the optimization of such multi-source multi-channel live streaming network. We first formulate the problem which comprehensively and realistically captures various delay and bandwidth components, and show that it is NP-hard. We then propose an efficient algorithm called COMMOS (Collaborative Multi-source Multi-channel Streaming Overlay) which achieves low channel delay. Extensive simulation results based on real Internet topologies show that COMMOS outperforms other state-of-the-art schemes by a wide margin (often by more than 40%), due to its better utilization of network resources.