Abstract:
Recent measurements of packet/cell streams in multimedia communication networks have revealed that they have the self-similar property and are of different character istics from traditional traffic streams. Therefore, a number of studies of modeling the self-similar traffic have been performed. In this paper, we first give some definitions of self-similarity. Then, we propose a fitting method for the self-similar traffic in terms of Markov-modulated Poisson process (MMPP). We construct an MMPPas the superposition of two-state MMPPs and fit it so as to match the variance function over several time-scales. Numerical examples show that the variance function of the self-similar process can be well represented by that of four-state MMPP. We also examine the queueing behavior of the resulting MMPP/D/1 queueing systems. We compare the results with the simulation for the queueing systems with the self-similar process as an input.