AN APPROXIMATE MODEL FOR PERFORMANCE EVALUATION OF REAL-TIME MULTIMEDIA COMMUNICATION-SYSTEMS

A Markov Modulated Poisson Process (MMPP) is a doubly stochastic Poisson process which has recently received a lot of attention due to its ability to model a highly correlated arrival stream while retaining analytical tractability. In this paper, the cell-arrival process from integrated voice and data sources is approximated by a two-state MMPP with batch arrivals (BMMPP). We propose a new matching technique which leads to more accurate performance prediction than other recent work for both delay estimation and evaluation to tail probabilities. While using BMMPP in the model does not noticeably increase the computational complexity over MMPP, it allows better representation of traffic sources with significantly higher burstiness. Another major contribution of the proposed model is its simplicity which makes the model suitable for real-time traffic control. An extended version of the model for integrated video, voice and data sources is also given with numerical examples again showing that the accuracy is quite satisfactory.