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Estimating the Intensity of Long-Range Dependence in Real and Synthetic Traffic Traces

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Book cover Computer Networks (CN 2015)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 522))

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Abstract

This paper examines various techniques for estimating the intensity of Long-Range Dependence (LRD). Trial data sets with LRD are generated using Fractional Gaussian noise and Markov modulated Poisson process. The real data set collected in IITiS PAN is also used.

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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

    Joanna Domańska & Tadeusz Czachórski

  2. Institute of Informatics, Silesian Technical University, Akademicka 16, 44-100, Gliwice, Poland

    Adam Domański

Authors
  1. Joanna Domańska
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  2. Adam Domański
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  3. Tadeusz Czachórski
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Correspondence to Tadeusz Czachórski .

Editor information

Editors and Affiliations

  1. Silesian University of Technology, Gliwice, Poland

    Piotr Gaj

  2. Silesian University of Technology, Gliwice, Poland

    Andrzej Kwiecień

  3. Silesian University of Technology, Gliwice, Poland

    Piotr Stera

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Domańska, J., Domański, A., Czachórski, T. (2015). Estimating the Intensity of Long-Range Dependence in Real and Synthetic Traffic Traces. In: Gaj, P., Kwiecień, A., Stera, P. (eds) Computer Networks. CN 2015. Communications in Computer and Information Science, vol 522. Springer, Cham. https://doi.org/10.1007/978-3-319-19419-6_2

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  • DOI: https://doi.org/10.1007/978-3-319-19419-6_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-19418-9

  • Online ISBN: 978-3-319-19419-6

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