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Hidden Markov Models in Long Range Dependence Traffic Modelling

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Distributed Computer and Communication Networks (DCCN 2017)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 700))

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Abstract

Hidden Markov Models (HMM) have been widely used in several areas of computer science. Conventional HMMs are well-known for their efficiency in modeling short-term dependencies between adjacent elements, but some researchers concluded that they cannot grasp long-range interactions between distant elements. Long-range dependence (LRD) of data refers to temporal similarity present in the data. Various studies demonstrated the presence of LRD at network traffic on several levels of communications protocols. This paper concerns the HMM-traffic source capability to capture the LRD appeared in real network traffic. We used several estimators of Hurst parameter to evaluate the LRD. Not all LRD processes mandatorily have a definable Hurst parameter, but the value of H between 0.5 and 1 is usually considered the standard measure of LRD.

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Author information

Authors and Affiliations

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

    Adam Domański

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

    Joanna Domańska & Tadeusz Czachórski

Authors
  1. Joanna Domańska
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  2. Adam Domański
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  3. Tadeusz Czachórski
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Corresponding author

Correspondence to Joanna Domańska .

Editor information

Editors and Affiliations

  1. V.A. Trapeznikov Institute of Control Sciences, Russian Academy of Sciences, Moscow, Russia

    Vladimir M. Vishnevskiy

  2. RUDN University, Moscow, Russia

    Konstantin E. Samouylov

  3. V.A. Trapeznikov Institute of Control Sciences, Russian Academy of Sciences, Moscow, Russia

    Dmitry V. Kozyrev

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Domańska, J., Domański, A., Czachórski, T. (2017). Hidden Markov Models in Long Range Dependence Traffic Modelling. In: Vishnevskiy, V., Samouylov, K., Kozyrev, D. (eds) Distributed Computer and Communication Networks. DCCN 2017. Communications in Computer and Information Science, vol 700. Springer, Cham. https://doi.org/10.1007/978-3-319-66836-9_7

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  • DOI: https://doi.org/10.1007/978-3-319-66836-9_7

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-66835-2

  • Online ISBN: 978-3-319-66836-9

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