00000cab a22000003a 4500 UP-99796217609332658 Buklod 20231007234439.0 m |o d | ta 100608s xx d | ||r ||||| || DENGII eng Andersen, A.T. A Markovian approach for modeling packet traffic with long-range dependence. pp. 719-732 We present a simple Markovian framework for modeling packet traffic with variability over several time scales. We present a fitting procedure for matching second-order properties of counts to that of a second-order self-similar process. Our models essentially consist of superpositions of two-state Markov modulated Poisson processes (MMPPs). We illustrate that a superposition of four two-state MMPPs suffices to model second-order self-similar behavior over several time scales. Our modeling approach allows us to fit to additional descriptors while maintaining the second-order behavior of the counting process. We use this to match interarrival time correlations Markov modulated Poisson processes. Counting process. Fitting procedure. Four two-state MMPP. Interarrival time correlations. Long-range dependence. Packet traffic modelling. Second-order properties. Second-order self-similar process. Superpositions. Time scales. Two-state MMPP. IEEE Journal on selected areas in communications 16, 5 (1998). FO UPD DENG-II Article