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Extreme Value Analysis of Teletraffic Data


  • Tsourti, Zoi
  • Panaretos, John


An empirically verified characteristic of the expanding area of Internet is the longtailness of phenomena such as cpu time to complete a job, call holding times, files lengths requested, inter-arrival times and so on. Extreme values of the above quantities are liable to cause problems to the efficient operation of the network and call for effective design and management. Extreme-value analysis is an area of statistical analysis particularly concerned with the systematic study of extremes, providing useful insight to fields where extreme values are probable to occur and have detrimental effects, as is the case of teletraffics. In this paper we illustrate the main elements of this analysis and proceed to a detailed application of extreme-value analysis concepts to a specific teletraffic data set. This analysis verifies, too, the existence of long tails in the data.

Suggested Citation

  • Tsourti, Zoi & Panaretos, John, 2004. "Extreme Value Analysis of Teletraffic Data," MPRA Paper 6391, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:6391

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    References listed on IDEAS

    1. Einmahl, J. H.J. & Dekkers, A. L.M. & de Haan, L., 1989. "A moment estimator for the index of an extreme-value distribution," Other publications TiSEM 81970cb3-5b7a-4cad-9bf6-2, Tilburg University, School of Economics and Management.
    2. Jón Daníelsson & Casper G. de Vries, 1998. "Beyond the Sample: Extreme Quantile and Probability Estimation," Tinbergen Institute Discussion Papers 98-016/2, Tinbergen Institute.
    3. M. I. Barão & J. A. Tawn, 1999. "Extremal analysis of short series with outliers: sea-levels and athletics records," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 48(4), pages 469-487.
    4. Tsourti, Zoi & Panaretos, John, 2001. "Extreme Value Index Estimators and Smoothing Alternatives: Review and Simulation Comparison," MPRA Paper 6384, University Library of Munich, Germany.
    5. McNeil, Alexander J., 1997. "Estimating the Tails of Loss Severity Distributions Using Extreme Value Theory," ASTIN Bulletin: The Journal of the International Actuarial Association, Cambridge University Press, vol. 27(01), pages 117-137, May.
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    Cited by:

    1. Lorenzo Hern'andez & Jorge Tejero & Alberto Su'arez & Santiago Carrillo-Men'endez, 2012. "Percentiles of sums of heavy-tailed random variables: Beyond the single-loss approximation," Papers 1203.2564,, revised Dec 2012.

    More about this item


    Teletraffic engineering; Long tails; Extreme-value index; Smoothing procedures;

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General


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