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In order to maintain consistent quality of service, computer networkengineers face the task of monitoring the traffic fluctuations on theindividual links making up the network. However, due to resource constraintsand limited access, it is not possible to directly measure all the links.Starting with a physically interpretable probabilistic model of network-widetraffic, we demonstrate how an expensively obtained set of measurements may beused to develop a network-specific model of the traffic across the network.This model may then be used in conjunction with easily obtainable measurementsto provide more accurate prediction than is possible with only the inexpensivemeasurements. We show that the model, once learned may be used for the samenetwork for many different periods of traffic. Finally, we show an applicationof the prediction technique to create relevant control charts for detection andisolation of shifts in network traffic.

Network-wide Statistical Modeling and Prediction of Computer Traffic