Effective bandwidth based scheduling for streaming multimedia

We propose a class of packet scheduling algorithms for streaming media. The importance level of a video packet is determined by its relative position within its group of pictures, taking into account the motion-texture discrimination and temporal scalability. We generate a number of nested substreams, with more important streams embedding less important ones in a progressive manner. We model the streaming system as a queueing system, compute the run-time decoding failure probability of a frame in each substream based on effective bandwidth, and determine the optimum substream to be sent at any moment in time. The data within optimum substream is sent based on earliest-deadline-first scheduling, until the next channel report arrives, at which time the optimum substream is recomputed. From experiments with real video data, we show that our proposed scheduling scheme outperforms the conventional sequential sending scheme.