Deriving traffic demands for operational IP networks: methodology and experience
Proceedings of the conference on Applications, Technologies, Architectures, and Protocols for Computer Communication
Traffic matrix estimation: existing techniques and new directions
Proceedings of the 2002 conference on Applications, technologies, architectures, and protocols for computer communications
Fast accurate computation of large-scale IP traffic matrices from link loads
SIGMETRICS '03 Proceedings of the 2003 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
An information-theoretic approach to traffic matrix estimation
Proceedings of the 2003 conference on Applications, technologies, architectures, and protocols for computer communications
Traffic matrix estimation based on a square root Kalman filtering algorithm
International Journal of Network Management
Throughput optimisation of inter- and intra-domain autonomous systems traffic engineering
International Journal of Communication Networks and Distributed Systems
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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.