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Practical Time-Scale Fitting of Self-Similar Traffic with Markov-Modulated Poisson Process

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Abstract

Recent measurements of packet/cell streams in multimedia communication networks have revealed that they have the self-similar property and are of different characteristics from traditional traffic streams. In this paper, we first give some definitions of self-similarity. Then, we propose a fitting method for the self-similar traffic in terms of Markov-modulated Poisson process (MMPP). We construct an MMPP as the superposition of two-state MMPPs and fit it so as to match the variance function over several time-scales. Numerical examples show that the variance function of the self-similar process can be well represented by that of resulting MMPPs. We also examine the queueing behavior of the resulting MMPP/D/1 queueing systems. We compare the analytical results of MMPP/D/1 with the simulation ones of the queueing system with self-similar input.

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Authors and Affiliations

  1. NTT Information Sharing Platform Laboratories, 3-9-11 Midori-cho, Musashino-shi, Tokyo, 180-8585, Japan

    Tadafumi Yoshihara

  2. Graduate School of Information Science, Nara Institute of Science and Technology, 8916-5 Takayama, Ikoma, Nara, 630-0101, Japan

    Shoji Kasahara & Yutaka Takahashi

Authors
  1. Tadafumi Yoshihara
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  2. Shoji Kasahara
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  3. Yutaka Takahashi
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Yoshihara, T., Kasahara, S. & Takahashi, Y. Practical Time-Scale Fitting of Self-Similar Traffic with Markov-Modulated Poisson Process. Telecommunication Systems 17, 185–211 (2001). https://doi.org/10.1023/A:1016616406118

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  • DOI: https://doi.org/10.1023/A:1016616406118

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