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Can self-similar traffic be modeled by Markovian processes?

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Broadband Communications Networks, Services, Applications, Future Directions (IZS 1996)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1044))

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Abstract

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.

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Authors and Affiliations

  1. EPFL - DI - LRC, CH-1015, Lausanne, Switzerland

    Stephan Robert & Jean-Yves Le Boudec

Authors
  1. Stephan Robert
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  2. Jean-Yves Le Boudec
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Bernhard Plattner

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© 1996 Springer-Verlag Berlin Heidelberg

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Robert, S., Le Boudec, JY. (1996). Can self-similar traffic be modeled by Markovian processes?. In: Plattner, B. (eds) Broadband Communications Networks, Services, Applications, Future Directions. IZS 1996. Lecture Notes in Computer Science, vol 1044. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0022222

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  • DOI: https://doi.org/10.1007/BFb0022222

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-60895-0

  • Online ISBN: 978-3-540-49669-4

  • eBook Packages: Springer Book Archive

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