Clustering method and semi-Markov processes for VBR traffic modeling in an ATM network

In this paper we present a framework for modeling computer network variable-bit-rate (VBR) traffic based on a semi-Markov processes. We propose an algorithm based on a simple clustering method to build semi-Markov models for computer network traffic modeling. We introduce our novel mechanism by giving its detailed algorithm, and later analyze its performance by means of simulation. We reveal the efficacy of the proposed method for long-range dependence (LRD) traffic modeling under realistic buffer sizes, and compare the performance of a real computer network VBR traffic trace with the synthesized traces obtained using our mechanism.