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Workshop on Traffic Management and Traffic Engineering for the Future Internet

FITraMEn 2008: Traffic Management and Traffic Engineering for the Future Internet pp 141–154Cite as

Blind Maximum-Likelihood Estimation of Traffic Matrices in Long Range Dependent Traffic

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Part of the book series: Lecture Notes in Computer Science ((LNCCN,volume 5464))

Abstract

A method is proposed to estimate traffic matrices in the presence of long-range dependent traffic, while the methods proposed so far for that task have been designed for short-range dependent traffic. The method employs the traffic measurements on links and provides the maximum likelihood estimate of both the traffic matrix and the Hurst parameter. It is “blind”, i.e. it does not exploit any model neither for the traffic intensity values (e.g. the gravity model) nor for the mean-variance relationship (e.g. the power-law model). In the application to a sample network the error on traffic intensities decays rapidly with the traffic intensity down to below 30%. The estimation error of the Hurst parameter can be reduced to a few percentage points with a proper choice of the measurement interval.

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Author information

Authors and Affiliations

  1. Dip. di Statistica, Probabilità e Statistiche Applicate, Università di Roma “La Sapienza”, Piazzale Aldo Moro, Rome, Italy

    Pier Luigi Conti

  2. Università LUMSA, Piazza delle Vaschette 101, Rome, Italy

    Livia De Giovanni

  3. Dip. di Informatica, Sistemi e Produzione, Università di Roma “Tor Vergata”, Via del Politecnico 1, Rome, Italy

    Maurizio Naldi

Authors
  1. Pier Luigi Conti
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  2. Livia De Giovanni
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  3. Maurizio Naldi
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Editor information

Editors and Affiliations

  1. Instituto de Telecomunicacoes, Instituto Superior Technico, Av. Rovisco Pais, 1049-001, Lisboa, Portugal

    Rui Valadas

  2. Instituto de Telecomunicacoes, Universidade de Aveiro, Campus de Santiago, 3810-193, Aveiro, Portugal

    Paulo Salvador

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© 2009 Springer-Verlag Berlin Heidelberg

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Conti, P.L., De Giovanni, L., Naldi, M. (2009). Blind Maximum-Likelihood Estimation of Traffic Matrices in Long Range Dependent Traffic. In: Valadas, R., Salvador, P. (eds) Traffic Management and Traffic Engineering for the Future Internet. FITraMEn 2008. Lecture Notes in Computer Science, vol 5464. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04576-9_10

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  • DOI: https://doi.org/10.1007/978-3-642-04576-9_10

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-04575-2

  • Online ISBN: 978-3-642-04576-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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