Efficient simulation of cell loss probability in ATM networks with heterogeneous connection traffic descriptors

Abstract

In ATM networks, the purpose of connection admission control is to decide if allowing a nrw connection into the network violates a quality of service measure of the new connection or the existing connections. Instead of using statistical traffic models, we represent the connection entering the network by the connection traffic descriptors standardized by the ATM Forum and used by the connection admission control algorithms. In this paper, we examine traffic sources described by heterogeneous connection traffic descriptors in order to analyze constant bit rate sources versus variable bit rate sources, as well as different classes of variable bit rate sources. We use Monte Carlo simulation to estimate the cell loss probability of the combined traffic stream, as well as the individual classes using both random buffer filling and priority buffer filling schemes. Importance sampling is used to increase the efficiency of the simulation. For the experimental example considered here, the improvement in simulation efficiency compared to conventional Monte Carlo simulation is inversely proportional t o the estimate.'

Simulation of rare events in communications networks

“…Parametric IS methods are not very effective when the randomness in the system is described by a uniform probability distributions. Conditional biasing is an impor- tance sampling technique that has been shown to be effective in such cases [10,11]. However, conditional biasing does require some prior knowledge of the system behavior that causes the important event of interest.…”

“…The simulation overhead involved with the technique is negligible. See [10,11] for more complete descriptions of the use of conditional biasing in estimating cell loss, cell delay, and cell delay variation, respectively, in ATM networks.…”