Standard core of communications’ networks is represent by active elements, which carries out the processing of transmitted data units. Based on the results of the processing the data are transmitted from sender to recipient. The hardest challenge of the active elements present to determine what the data processing unit and what time of the system to match the processing priority assigned to individual data units. Based on the analysis of the architecture and function of active network components and algorithms, artificial neural networks can be assumed to be effectively useable to manage network elements. This article focuses on the design and use of the selected type of artificial neural network (Hopfield neural network) for the optimal management of network switch.
The speed of development of the computer network is an urgent need to comprehensively improve and optimize the overall performance of the network. Neural network algorithm has a massively parallel processing and distributed information storage, Hopfield neural network showed a unique advantage in the associative memory and optimization based on the neural network algorithm for computer network optimization model of Hopfield neural network theory and reality computer network, modern optimization methods, it is combined.
Progressive optimization methods for applied in computer network