摘要 : Accurate MPEG source models are needed to support high speed networks such as ATM and Internet. In this paper, we propose a video model called Gaussian auto-regressive and chi-square processes (GACS) for MPEG coded video traffic. ... 展开 Accurate MPEG source models are needed to support high speed networks such as ATM and Internet. In this paper, we propose a video model called Gaussian auto-regressive and chi-square processes (GACS) for MPEG coded video traffic. The GACS models the sizes of MPEG I, P, and B frames according to the MPEG syntax I-frame>P-frame>B-frame. This is done by decomposing the process of each frame size into a weighted sum of a number of chi-square sequences. Each chi-square sequence is then obtained by squaring a Gaussian process, which is efficiently generated by using an auto-regressive (AR) model whose parameters are determined from an estimated covariance matrix. We evaluate the effectiveness of our model by conducting a series of experiments using a wide variety of long empirical video sequences. The results show that the proposed model leads to excellent data fit and accurate prediction of queuing performance. 收起