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