Accurate analytical model for MPEG coded video traffic

Traffic generated by video applications is increasingly cramming existing networks, and it is thus essential to accurately characterize video traffic for efficient network management. Traditional models, however, fall short in describing video traffic which is strongly autocorrelated and bursty. hence, autocorrelations among data should be taken into consideration. Self-similar processes, modulated according to the Motion Picture Experts Group group of pictures (MPEG GOP) structure, are proposed to accurately capture the short range dependency (SRD) and long range dependency (LRD) of MPEG video traffic.