Efficient modeling of VER MPEG-1 coded video sources

Performance evaluation of broadband networks requires statistical analysis and modeling of the actual network traffic. Since multimedia services, and especially variable bit rate (VBR) MPEG-coded video streams are expected to be a major traffic component carried by these networks, modeling of such s ervices and accurate estimation of network resources are crucial for proper network design and congestion-control mechanisms that can guarantee the ne gotiated quality of service at a minimum cost. The layer modeling of MPEG-1 coded video streams and statistical analysis of their traffic characterist ics at each layer is proposed in this paper, along with traffic models capa ble of estimating the network resources over asynchronous transfer mode (AT M) links. First, based on the properties of the entire MPEG-1 sequence (fra me layer signal), a model (Model A) is presented by correlating three stoch astic processes in discrete time (autoregressive models), each of which cor responds to the three types of frames of the MPEG encoder (I, P, and B fram es). To simplify the traffic Model A and to reduce the required number of p arameters, we study the MPEG stream at a higher layer by considering a sign al, which expresses the average properties of I, P, and B frames over a gro up of picture (GOP) period. However, models on this layer cannot accurately estimate the network resources, especially in multiplexing schemes. For th is reason, an intermediate layer is introduced, which exploits and efficien tly combines information of both the aforementioned layers, producing a mod el (Model B), which requires much smaller number of parameters than Model A and simultaneously provides satisfactory results as far as the network res ources are concerned. Evaluation of the validity of the proposed models is performed through experimental studies and computer simulations, using seve ral long duration VER MPEG-1 coded sequences, different from that used in m odeling. The results indicate that both Models A and B are good estimators of video traffic behavior over ATM links at a wide range of utilization.