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Network delay tomography using flexicast experiments

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  • Earl Lawrence
  • George Michailidis
  • Vijayan N. Nair

Abstract

Summary. Estimating and monitoring the quality of service of computer and communications networks is a problem of considerable interest. The paper focuses on estimating link level delay distributions from end‐to‐end path level data collected by using active probing experiments. This is an interesting large scale statistical inverse (deconvolution) problem. We describe a flexible class of probing experiments (‘flexicast’) for data collection and develop conditions under which the link level delay distributions are identifiable. Maximum likelihood estimation using the EM algorithm is studied. It does not scale well for large trees, so a faster algorithm based on solving for local maximum likehood estimators and combining their information is proposed. The usefulness of the methods is illustrated on real voice over Internet protocol data that were collected from the University of North Carolina campus network.

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  • Earl Lawrence & George Michailidis & Vijayan N. Nair, 2006. "Network delay tomography using flexicast experiments," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 68(5), pages 785-813, November.
    • Handle: RePEc:bla:jorssb:v:68:y:2006:i:5:p:785-813
    DOI: 10.1111/j.1467-9868.2006.00567.x
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    Cited by:

    1. Comert, Gurcan, 2013. "Effect of stop line detection in queue length estimation at traffic signals from probe vehicles data," European Journal of Operational Research, Elsevier, vol. 226(1), pages 67-76.

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