A MAP Fitting Method to Approximate
Real Traffic Behavior

András Horváth, Gergo István Rózsa, Miklós Telek

Abstract:

This paper provides a heuristic fitting method to capture some important features of real traffic sources by a Markovian arrival process (MAP). The novelty of the proposed approach lies in the separate treating of short and long range behavior of the considered traffic sources. The proposed MAP is the superposition of two elementary processes. A Phase type renewal process, whose interarrival time exhibits heavy-tail behavior over some time scales, is used to capture the long range dependent behavior, i.e., the empirical Hurst parameter. While a two-state Markov modulated Poisson process (MMPP) is applied to approximate the short range behavior. Different analysis techniques are used to evaluate the goodness of the proposed fitting method.

Postscript

[Publications of András Horváth]