Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/17848
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Type: Journal article
Title: Estimating point-to-point and point-to-multipoint traffic matrices: An information-theoretic approach
Author: Zhang, Y.
Roughan, M.
Lund, C.
Donoho, D.
Citation: IEEE - ACM Transactions on Networking, 2005; 13(5):947-960
Publisher: IEEE-Inst Electrical Electronics Engineers Inc
Issue Date: 2005
ISSN: 1063-6692
Statement of
Responsibility: 
Yin Zhang, Member, Matthew Roughan, Carsten Lund, and David L. Donoho
Abstract: Traffic matrices are required inputs for many IP network management tasks, such as capacity planning, traffic engineering, and network reliability analysis. However, it is difficult to measure these matrices directly in large operational IP networks, so there has been recent interest in inferring traffic matrices from link measurements and other more easily measured data. Typically, this inference problem is ill-posed, as it involves significantly more unknowns than data. Experience in many scientific and engineering fields has shown that it is essential to approach such ill-posed problems via "regularization". This paper presents a new approach to traffic matrix estimation using a regularization based on "entropy penalization". Our solution chooses the traffic matrix consistent with the measured data that is information-theoretically closest to a model in which source/destination pairs are stochastically independent. It applies to both point-to-point and point-to-multipoint traffic matrix estimation. We use fast algorithms based on modern convex optimization theory to solve for our traffic matrices. We evaluate our algorithm with real backbone traffic and routing data, and demonstrate that it is fast, accurate, robust, and flexible.
Keywords: Failure analysis; information theory; minimum mutual information; point-to-multipoint; point-to-point; regularization; SNMP; traffic engineering; traffic matrix estimation
Description: © 2005 IEEE.
RMID: 0020051245
DOI: 10.1109/TNET.2005.857115
Appears in Collections:Applied Mathematics publications

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