Study of the impact of MPEG-1 correlations on video-sources statistical multiplexing

Variable bit-rate (VBR) video is expected to become increasingly important with the large scale deployment of broadband-integrated services networks (B-ISDNs). While the modeling of VBR video sources has received significant attention, there is no widely accepted model which lends itself to mathematical analysis. Furthermore, new video compression standards are emerging, such as the MPEG family. A detailed statistical analysis of a long sample of a movie encoded with an MPEG-1 algorithm highlights that traffic generated by an MPEG-1 encoder has both a high degree of burstiness (peak/average ratio greater than five) and a strong long-term correlation (positive correlation lasts for ten/twenty minutes). In this paper, we propose and analyze a Markov model which captures both the burstiness and the temporal dependencies of MPEG traffic. Furthermore, we show that our model is a flexible traffic generator which is suitable for studying statistical multiplexing issues. Specifically, we study both the multiplexing of a VBR video source with low priority traffic and the multiplexing of several VBR video sources. The results obtained show that the long-term correlation significantly affects the tail of the delay distribution even for lightly loaded networks. The presence of a long range dependence in the MPEG traffic significantly reduces the gain in terms of network utilization which can be achieved with statistical multiplexing of i.i.d. sources.