Institute of Mathematical Statistics Lecture Notes - Monograph Series

An iterative tomogravity algorithm for the estimation of network traffic

Jiangang Fang, Yehuda Vardi, Cun-Hui Zhang

Abstract

This paper introduces an iterative tomogravity algorithm for the estimation of a network traffic matrix based on one snapshot observation of the link loads in the network. The proposed method does not require complete observation of the total load on individual edge links or proper tuning of a penalty parameter as existing methods do. Numerical results are presented to demonstrate that the iterative tomogravity method controls the estimation error well when the link data is fully observed and produces robust results with moderate amount of missing link data.

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Primary Subjects: 62P30, 62H12, 62G05, 62F10
Keywords: network traffic flow; network tomography; Kullback-Leiber distance; network gravity model; regularized estimation
Full-text: Open access
Links and Identifiers

Permanent link to this document: http://projecteuclid.org/euclid.lnms/1196794940
Digital Object Identifier: doi:10.1214/074921707000000030

2012 © Institute of Mathematical Statistics

Institute of Mathematical Statistics Lecture Notes - Monograph Series

Institute of Mathematical Statistics Lecture Notes - Monograph Series