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Internet Traffic Source Based on Hidden Markov Model

  • Joanna Domańska
  • Adam Domański
  • Tadeusz Czachórski
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6869)

Abstract

This article shows how to use Hidden Markov Models to generate self-similar traffic. The well-known Bellcore traces are used as a training sequence to learn HMM model parameters. Performance of trained model are tested on the remaining portions of the sequences.Then we can use the HMM trained with the Bellcore data as the traffic source model.

Keywords

Hide Markov Model Vector Quantization Fractional Brownian Motion Interarrival Time Hurst Parameter 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Joanna Domańska
    • 1
  • Adam Domański
    • 2
  • Tadeusz Czachórski
    • 1
    • 2
  1. 1.Institute of Theoretical and Applied InformaticsPolish Academy of SciencesGliwicePoland
  2. 2.Institute of InformaticsSilesian Technical UniversityGliwicePoland

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