MMPP models for multimedia traffic

The paper presents a study on the use of Markov-Modulated Poisson Processes (MMPP's) for characterizing multimedia traffic with short-term and long-te rm correlation. The applicability of the 2-state MMPP and a refined moment- based parameter-matching technique to model an arbitrary ATM traffic stream in evaluating its queueing performance are examined by simulation. Followi ng a discussion on the limitation of the 2-state MMPP model, a model using a superposition of N homogeneous 2-state MMPP to characterize bursty multim edia traffic is presented. The proposed model requires only five parameters which can be estimated from the samples of the traffic counting process by using a pdf-based matching technique. The introduced pdf-based parameter-m atching procedure uses the probability density function of the arrival rate and the IDC curve of the traffic samples. An approximation for the probabi lity of loss in MMPP/D/1 queues is also obtained. The versatility and accur acy of the proposed model to characterize bursty multimedia traffic are sho wn by several case studies and test results.