Modeling and simulation of self-similar variable bit rate compressed video

Abstract

Variable bit rate (VBR) compressed video is expected to become one of the major loading factors in high-speed packet networks such as ATM-based B-ISDN. However, recent measurements based on long empirical traces (complete movies) revealed that VBR video traffic possesses self-similar (or fractal) characteristics, meaning that the dependence in the traffic stream lasts much longer than traditional models can capture.In this paper, we present a unified approach which, in addition to accurately modeling the marginal distribution of empirical video records, also models directly both the short and the long-term empirical autocorrelation structures. We also present simulation results using synthetic data and compare with results based on empirical video traces.Furthermore, we extend the application of efficient estimation techniques based on importance sampling that we had used before only for simple fractal processes. We use importance sampling techniques to efficiently estimate low probabilities of packet losses that occur when a multiplexer is fed with synthetic traffic from our self-similar VBR video model.