Can self-similar traffic be modeled by Markovian processes?

  • Stephan Robert
  • Jean-Yves Le Boudec
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1044)


In this paper, we compare high time resolution local area network (LAN) traffic with three different traffic models: Poisson, ON-OFF and 5-state Markov process. Due to the measured data's extreme variability on time scales ranging from milliseconds to days, it is difficult to find a model for it, especially a Markovian one. Recent studies show that conventional models do not capture the characteristics of the observed traffic. Fractal-based models have already been built to characterize such a traffic but they are not easily tractable tractability of them is not great. Through a new method which integrates different time scales in the model, we have tried to find a quite simple Markovian process having the same behavior as the measured traffic on the LAN. We show in particular that a simple 5-state Markov process integrating different time scales can reasonably model the behavior of measured traffic up to a certain time interval.


LAN Traffic self-similar Markovian models long range dependences 


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Copyright information

© Springer-Verlag Berlin Heidelberg 1996

Authors and Affiliations

  • Stephan Robert
    • 1
  • Jean-Yves Le Boudec
    • 1
  1. 1.EPFL - DI - LRCLausanneSwitzerland

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