Adaptive sampling in measuring traffic parameters in a computer network using a fuzzy regulator and a neural network

Adaptive sampling using a neural network and a fuzzy regulator is described as applied to computer network traffics. The objective of this approach is to maximally reduce the amount of data to be processed with preservation of acceptable measurement accuracy. The results of experimental verification of sampling efficiency are also presented that are based on the traffic data archive of a real computer network.