A new traffic model for MPEG encoded videos in ATM networks

This paper presents a new traffic model for MPEG encoded video sequences. Two second-order autoregressive (AR) processes are used to model the autocorrelation structure. One AR process is used to generate the mean frame size of the scenes to model the long range dependence and another AR process is used to generate the fluctuations within the scenes to model the short range dependence. The scene length distribution is fitted using a geometric distribution. The first AR process is therefore “stretched” unevenly according to the geometric distribution to generate the mean frame size sequence. The two AR processes are not simply superposed; instead, they are nested with each other. The parameters of the AR processes are estimated from measurements of empirical video sequences. Simulation results show that the present model captures the autocorrelation structure in the empirical traces for both small and large lags. The MPEG traffic model presented in this paper is used to predict the queueing performance of single and multiplexed MPEG video sequences at an asynchronous transfer mode multiplexer. Comparison study shows that the present model provides accurate prediction for quality of service measures such as cell loss ratio under different traffic loads and various buffer sizes