Lucent Technologies Inc.

Bin Yu

Jin Cao

Dawei Huang

Scott Alan Vander Wiel

R Drew Davis

In many packetized communication networks, it is not feasible to obtain exact counts of traffic (OD counts) between specific origin-destination node pairs, because the link counts that are readily obtainable at router interfaces are aggregated indiscriminately over OD pairs. The best that can be done is to make a probabilistic inference concerning the OD counts from the observed link counts. Such an inference relies upon a known linear relationship between observed link counts and unknown OD counts, and a statistical model describing how the values of the OD and link counts are probabilistically distributed. Disclosed is an improved method for making such inferences. The disclosed method takes explicit account of past data when forming a current estimate of the OD counts. As a consequence, behavior that evolves in time is described with improved accuracy and smoothness.

Method for estimating the traffic matrix of a communication network

A lossless encoding methodology is described based on residual coding techniques and using a modified Least Mean Squares methodology to develop a predictor for a signal to be encoded, and a residual as the difference between the signal and its predicted value. After the residual for an input signal segment is obtained according to the method of the invention, that method is again applied to the residual value process to develop a second predictor, from which a second residual value is obtained. The method is then applied for at least one further iteration to the most recently obtained residual value process to develop a third predictor for the signal to be encoded. A single prediction value is then selected as a statistical representative of those multiple predictor values. The residual value to be used for encoding the input signal increment is determined as the difference between the signal value and the selected predictor value.

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Berkeley, CA, United States of America

Bin Yu