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Origin-Destination Network Tomography with Bayesian Inversion Approach

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1 Author(s)
Jianzhong Zhang ; Xiamen University, China

Origin-destination (OD) network tomography problem is the estimation of OD traffic counts from measurable traffic counts at router interfaces. In this paper the problem is formulated as a linear inverse problem with additive noise and is resolved using Bayesian inversion approach. Both OD traffic counts and noise are modelled as Gaussian random functions, and are represented by Karhunen-Loeve expansion, respectively. The posterior random function of OD traffic counts given the link counts is also represented as the Karhunen-Loeve expansion. With the singular system of routing matrix, we thus can found the optimal estimator of OD traffic counts analytically

Published in:

2006 IEEE/WIC/ACM International Conference on Web Intelligence (WI 2006 Main Conference Proceedings)(WI'06)

Date of Conference:

18-22 Dec. 2006