Fanout Inference from Link Count

Abstract

The traffic matrix is the fundamental input data in network planning, simulation and traffic engineering. However, it is often unknown and its direct measurement with devices such as Netflow is a too heavy process for large high-speed networks. The estimation of the traffic matrix from link counts appears as the best alternative approach. Recent works assume that prior information do not allow alone an accurate estimation of the traffic matrix so they are using Netflow measures to calibrate their model. These models assume spatial and temporal relations between different instants of measure. We show in this paper that we can obtain similar error rates without this costly calibration phase thanks to a spatial and temporal relation introduced in K. Papagiannaki et al. (2004)