ATM network models for traffic management

Abstract

ATM traffic modeling is a rapidly developing research area. In order to test and evaluate the performance of ATM networ s and switches, modeling stochastic processes with various distributions is required. Cellular Automaton (CA) can produce effective pseudo-random bit streams since there is little correlation among CA cells and can effectively generate random patterns which have good randomness characteristics. OPtimized Network Engineering Tool (OPNET) provides a comprehensive development environment supporting the modeling of communication protocols, networks and distributed systems. Both behavior and performance of modeled systems can be analyzed by performing discrete event simulations. OPNET provides an opportunity to examine the higher level and more complex behavior of ATM networks. In this thesis, OPNET is used to model ATM networks; the modeled ATM networks are used to investigate congestion and OPNET limitation; and CA is used for generating random distributions for ATM traffic. The significance and contributions of this thesis are: (1) making the first step to use CA to generate traffic distributions; (2) designing a model of a real network; and (3) proving that OPNET is a suitable tool for modeling and simulation of ATM networks, and three factors: imbalance traffic load, insufficient buffer size and bursty traffic, can cause congestion. (Abstract shortened by UMI.)