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Evaluation of output traffic from an ATM-node

How is a traffic process changed, after it has passed a node in the ATM network? We focus on the change in two parameters: auto-correlation and coefficient of variation of inter-arrival times: The decrease in the one leads to an increase in the other. We find an empirical approximate linear relation. The method presented in this paper yields a fast algorithm for computing the two parameters all over the queueing network. The complexity resides in the approximation of a stochastic process to the parameters and subsequently solving the queueing model. We approximate a Switched Poisson Process (SPP) to these parameters and find, that the parameters, that we focus on, enable us to calculate accurately the performance of the queues in a network. As the parametric model is empirically based, and because we have no analytical base for it, we have chosen it to be rather rough. Additionally the SPP has its modelling limitations. But the model is simple and can be improved, and other stochastic processes may supplement the SPP. Thus the paper indicates an untraditional way of making queueing network analysis.