Traffic modeling in a multi-media environment

Abstract

Proposes a new model for characterizing the data traffic in a multi-media environment. The authors model the data traffic by a two-state doubly stochastic Poisson process, with sojourn times in each state having an independent and identical heavy tailed distribution, such as the Pareto distribution. The simulation results from the new data traffic model are presented. The new model is versatile in capturing the self-similar characteristics of traffic found in the traffic measurements. The authors also suggest that the other two types of multi-media traffic namely, voice and video may each be characterized by a 2-state doubly stochastic Poisson process with exponential sojourn times (i.e., a Markov modulated Poisson process or MMPP).