Search for optimality in traffic matrix estimation : a rational approach by Cramer-Rao lower bounds

Abstract : In this paper we study the problem of traffic matrix estimation. The problem is ill-posed and thus some additional information has to be brought in to obtain an estimate. One common approach is to use the second moment statistics through a functional mean-variance relationship. We derive analytically the Fisher information matrix under this framework and obtain the Cramér-Rao lower bound (CRLB) for the variance of an estimator of the traffic matrix. Applications for the use of the CRLB are then demonstrated. From the bounds we can directly obtain confidence intervals for maximum likelihood estimates. Another use for the CRLB is the possibility to evaluate the efficiency of an estimator against the lower bound. A third possible application is to utilize bounds in an approach to find the best placement fordirect measurements of OD flows, so that it is optimal with regard to the traffic matrix estimation problem.
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Conference papers
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https://hal.archives-ouvertes.fr/hal-00504294
Contributor : Bibliothèque Télécom Bretagne <>
Submitted on : Tuesday, July 20, 2010 - 11:37:14 AM
Last modification on : Thursday, October 17, 2019 - 12:33:47 PM

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  • HAL Id : hal-00504294, version 1

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Paola Bermolen, Sandrine Vaton, I. Juva. Search for optimality in traffic matrix estimation : a rational approach by Cramer-Rao lower bounds. NGI'06 : 2nd Conference on Next Generation Internet Design and Engineering, Apr 2006, Valencia, Espagne. pp.224-231. ⟨hal-00504294⟩

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