Adaptive packet scheduling for scalable video streaming with network coding

Over the last decade, the emergence of new multimedia devices has motivated the research on efficient media streaming mechanisms that adapt to dynamic network conditions and heterogeneous devices' capabilities. Network coding as a rateless code has been applied to collaborative media streaming applications and brings substantial improvements regarding throughput and delay. However, little attention has been given to the recoverability of encoded data, especially for the streaming with a strict deadline. This in turn leads to severe quality of experience. In this paper, we solve the unrecoverable transmission by proposing a multi-generation packet scheduling problem, which is treated as a video quality maximization problem and solved using dynamic programming algorithm. Experimental results confirm that the proposed algorithm brings better data recoverability and better quality of service in terms of video quality, delivery ratio, lower redundancy rate under different network sizes.