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On Stochastic Models of Internet Traffic

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Information Technologies and Mathematical Modelling - Queueing Theory and Applications (ITMM 2015)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 564))

Abstract

The paper discusses various models of self-similar Internet traffic and techniques for estimating the intensity of Long-Range Dependence (LRD). In the experimental part real data sets collected in IITiS PAN are used together with synthetic LRD flows generated using Fractional Gaussian noise and Markov modulated Poisson processes. We are especially interested in Markov models since they can be incorporated in Markov queueing models, for which powerful analytical and numerical techniques are available.

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Author information

Authors and Affiliations

  1. Institute of Theoretical and Applied Informatics, Polish Academy of Sciences, Baltycka 5, 44–100, Gliwice, Poland

    Tadeusz Czachórski & Joanna Domańska

  2. Department of Information Engineering, University of Pisa, Via Caruso 16, 56122, Pisa, Italy

    Michele Pagano

Authors
  1. Tadeusz Czachórski
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  2. Joanna Domańska
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  3. Michele Pagano
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Corresponding author

Correspondence to Michele Pagano .

Editor information

Editors and Affiliations

  1. Applied Mathematics and Computer Science, Belarusian State University, Minsk, Russia

    Alexander Dudin

  2. Tomsk State University, Tomsk, Russia

    Anatoly Nazarov

  3. Kemerovo State University, Anzhero-Sudzhensk, Russia

    Rafael Yakupov

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Czachórski, T., Domańska, J., Pagano, M. (2015). On Stochastic Models of Internet Traffic. In: Dudin, A., Nazarov, A., Yakupov, R. (eds) Information Technologies and Mathematical Modelling - Queueing Theory and Applications. ITMM 2015. Communications in Computer and Information Science, vol 564. Springer, Cham. https://doi.org/10.1007/978-3-319-25861-4_25

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  • DOI: https://doi.org/10.1007/978-3-319-25861-4_25

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-25860-7

  • Online ISBN: 978-3-319-25861-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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