Title :
Origin-Destination Network Tomography with Bayesian Inversion Approach
Author :
Zhang, Jianzhong
Author_Institution :
Sch. of Inf. Sci. & Technol., Xiamen Univ.
Abstract :
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
Keywords :
Bayes methods; Gaussian processes; Karhunen-Loeve transforms; inverse problems; matrix algebra; random functions; telecommunication network routing; telecommunication traffic; Bayesian inversion approach; Gaussian random functions; Karhunen-Loeve expansion; OD traffic counts; additive noise; linear inverse problem; origin-destination network tomography; router interfaces; routing matrix; Additive noise; Bayesian methods; Distributed computing; Gaussian noise; Inverse problems; Random variables; Routing; Telecommunication traffic; Tomography; Traffic control;
Conference_Titel :
Web Intelligence, 2006. WI 2006. IEEE/WIC/ACM International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
0-7695-2747-7
DOI :
10.1109/WI.2006.126