Abstract— In a multi-source video streaming system, premature draining of low-power nodes can cause sudden failures of peer connections and degrade streaming performance. To solve this problem, we propose an energy-aware scheduling (EAS) scheme to better distribute the streaming load among different peers by jointly considering network conditions and node energy levels. We model the proposed scheme using a rate/energydistortion optimization framework and heuristically solve it using the concept of asynchronous clocks. Simulation studies show that the proposed EAS scheme can achieve comparable streaming quality while consuming less energy.
Danjue Li, Chen-Nee Chuah, Gene Cheung, S. J. Ben