J.-S.R. Lee, H.-W. Park (Korea), and H.-D.J. Jeong (New Zealand)
Long-Range Dependent Self-Similar Processes, Steady State Discrete-Event Simulation, Simulation Run-Length, Teletraffic, Telecommunication Networks
Recent studies of real teletraffic data in modern telecom munication networks have shown that teletraffic exhibits self-similar (or fractal) properties over a wide range of time scales. The properties of self-similar teletraffic are very different from the traditional models of teletraffic based on Poisson, Markov-modulated Poisson, and related pro cesses. The use of traditional models in networks char acterised by self-similar processes can lead to incorrect conclusions about the performance of analysed networks. In this paper, we examine queueing behaviour in steady state stochastic simulations of queueing systems with self similar inter-event input (i.e., queueing systems) and queueing systems. Assuming self-similar inter-event processes, many more observations are required to obtain the final simulation results with a re quired precision, as increases, than when assuming Pois son models, exhibiting SRD (i.e., queueing systems).
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