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Currently, cellular networks have become widespread, the operators of which simultaneously use the infrastructure of the second-generation GSM networks, DCS to build third-generation W-CDMA networks that provide broadband multiple access with code division. At the same time, the problem of providing high-speed Internet connections is exacerbated due to the growing volume of data of diverse types transmitted over the Internet. When testing the entire network coverage area, the total number of voice calls increases, so a method of long-term measurement of the bit rate of information transmission via wireless communication channels is proposed, which does not increase the service information in the network. Mathematical modeling of Internet traffic consumption using the proposed measurement method is performed and entropy estimates of information channel bandwidth are given.

The successful functioning of telecommunication networks largely depends on the effectiveness of algorithms for detection and protection against overloads. The article describes the main differences that arise when forecasting, monitoring and managing congestion at the node level and at the channel level. An algorithm for detecting congestion by estimating the entropy of time distributions of traffic parameters is proposed. The entropy measures of data sets for various types of model distribution, in particular for the Pareto distribution, which optimally describes the behavior of self-similar random processes, were calculated and analyzed. The advantages of this approach include scalability, sensitivity to changes in distributions of traffic characteristics and ease of implementation and accessible interpretation.

The analysis of the automatic control of water intake area of the pumping station, which is based on a controller with fuzzy logic and systematization using seasonally and hourly water consumption by using wavelet transforms.