Large-Scale IP Traffic Matrix Estimation Based on Fratar Model and ART

被引：0

作者：

Jiang, Dingde ^{[1
]}

He, Linbo ^{[2
]}

Chen, Jun ^{[2
]}

Hu, Guangmin ^{[1
]}

机构：

[1] UESTC, Key Lab Broadband Opt Fiber Transmiss & Commun Ne, Chengdu, Peoples R China

[2] Chengdu Univ Informat Technol, Dept Network Engn, Chengdu, Peoples R China

来源：

2007 INTERNATIONAL CONFERENCE ON WIRELESS COMMUNICATIONS, NETWORKING AND MOBILE COMPUTING, VOLS 1-15 | 2007年

基金：

中国国家自然科学基金;

关键词：

network tomography; traffic engineering; ART; Fratar model; traffic matrix;

D O I：

10.1109/WICOM.2007.478

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

This paper proposes a novel method of large-scale IP traffic matrix estimation, called FratarArt method by us, which is based on Fratar model and Algebraic Reconstruction Technique (ART). Firstly, we model OD flows as Fratar model and introduce the constrained relations between traffic matrix and link loads. At the same time, we consider the nonnegative constraints of traffic matrix. By Fratar model, we can get a good prior of network tomography. As a consequence, a good estimation of traffic matrix is attained with ART. Finally, we use the real data [1] in true network Abilene to validate our method. The results show that our method can perform fast the accurate estimation of traffic matrix and track its dynamics. In contrast to TomoGravtiy [2], our method improves remarkably and the estimation of traffic matrix is closer to real data.

引用

页码：1908 / +

页数：2

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