Global modeling of backbone network traffic

Authors:
Stilian Stoev;George Michailidis;Joel Vaughan
Affiliations:
Department of Statistics, University of Michigan, Ann Arbor, S. University;Department of Statistics & EECS, University of Michigan, Ann Arbor, S. University;Department of Statistics, University of Michigan, Ann Arbor, S. University
Venue:
INFOCOM'10 Proceedings of the 29th conference on Information communications
Year:
2010

Citing 14
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Abstract

We develop a probabilistic framework for globally modeling traffic over a computer network. The model integrates existing single-link (-flow) traffic models with the routing over the network to capture its behavior globally. It arises from a limit approximation of the traffic fluctuations as the time-scale and the number of users sharing the network grow. The resulting probability model is comprised of Gaussian and/or stable, infinite variance components. They can be succinctly described and handled by certain 'space-time' random fields. The model is validated against real data and applied to predict traffic fluctuations over unobserved links from a limited set of observed ones.