Modelling and performance analysis of traffic in ATM networks including autocorrelation

Non-renewal traffic appears in various shapes as the input to nodes in ATM networks. Adequate models of traffic types are required to analyze the performance of ATM switches. Among them are approaches assuming self-similarity, TES processes or semi-Markovian processes (SMP). We study approximate representations of traffic by semi-Markovian processes, which include autocorrelated arrival intervals depending on the states of an underlying Markov chain. The properties of the SMP autocorrelation function are derived, which are helpful to construct SMP adaptations. ATM switches with SMP input are analyzed using efficient algorithms for the discrete time SMP/G/1 queue. The method is applied to evaluate the performance of an ATM multiplexer with traffic superposed from a number of on-off sources.