An Assignment Model on Traffic Matrix Estimation

  • Tang Hong
  • Fan Tongliang
  • Zhao Guogeng
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4222)


It is important to acquire accurate knowledge of traffic matrices of networks for many traffic engineering or network management tasks. Direct measurement of the traffic matrices is difficult in large scale operational IP networks. One approach is to estimate the traffic matrices statistically from easily measured data. The performance of the statistical methods is limited due to they rely on the limited information and require large amount of computation, which limits the convergence of such computation. In this paper, we present an alternative approach to traffic matrix estimation. This method uses assignment model. The model is based on the link characters and includes a fast algorithm. The algorithm combines statistical and optimized tomography. The algorithm is evaluated by simulation and the simulation results show that our algorithm is robust, fast, flexible, and scalable.


Assignment Model Traffic Demand Traffic Engineering Traffic Matrix Link Load 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Tang Hong
    • 1
  • Fan Tongliang
    • 1
  • Zhao Guogeng
    • 1
  1. 1.Chongqing University of Post and TelecommunicationsChongqingChina

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