An accurate and treatable Markov model of MPEG-video traffic

An accurate and treatable Markov-based model for MPEG video traffic is proposed. Before reaching a definition of the model, a large number of MPEG video sequences are analyzed and their statistical characteristics are highlighted. Besides the well-known autocorrelation function, testifying the pseudo-periodicity of the sequence in the short term, and the gamma-shaped probability density function the correlation between different frames belonging to the same group of pictures (GOP) is also accurately studied. Then a structured model is proposed. Thanks to its two-level structure it is able to capture both the inter-GOP and the intra-GOP correlation. In order to obtain the first level of the model, the well-known inverse eigenvalue problem is solved in the discrete-time domain. Finally, the model is used to evaluate the loss probability in an ATM multiplexer loaded by an MPEG video source and an aggregate of external traffic. The accuracy of the model is evaluated by comparing the analytically obtained loss probability with the loss probability calculated by simulating the system using real traffic sequences as driven traces