Traffic matrix estimation on a large IP backbone: a comparison on real data

Gunnar, Anders and Johansson, Mikael and Telkamp, Thomas (2004) Traffic matrix estimation on a large IP backbone: a comparison on real data. In: Proceedings ACM Internet Measurement Conference, 2004, Taormina, Sicily, Italy.



This paper considers the problem of estimating the point-to-point traffic matrix in an operational IP backbone. Contrary to previous studies, that have used a partial traffic matrix or demands estimated from aggregated Netflow traces, we use a unique data set of complete traffic matrices from a global IP network measured over five-minute intervals. This allows us to do an accurate data analysis on the time-scale of typical link-load measurements and enables us to make a balanced evaluation of different traffic matrix estimation techniques. We describe the data collection infrastructure, present spatial and temporal demand distributions, investigate the stability of fan-out factors, and analyze the mean-variance relationships between demands. We perform a critical evaluation of existing and novel methods for traffic matrix estimation, including recursive fanout estimation, worst-case bounds, regularized estimation techniques, and methods that rely on mean-variance relationships. We discuss the weaknesses and strengths of the various methods, and highlight differences in the results for the European and American subnetworks.

Item Type:Conference or Workshop Item (Paper)
ID Code:218
Deposited By:Mr Ian Marsh
Deposited On:27 Feb 2008
Last Modified:18 Nov 2009 15:54

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