FIELD: communication.
SUBSTANCE: invention relates to the field of communication networks. In the method, statistical information received at the SDN application level is pre-processed: target features are selected therein and divided into the training and testing artificial neural network (ANN) of the sample. The process of training the ANN consists in calculating the initial values of the weighing coefficients of connections of the ANN layers and correcting said values. After the ANN is trained, the threshold values of the predicted features and, accordingly, the values of the output ANN layer are calculated. Based on the resulting predicted data of the output ANN layer, a control effect is generated using the selected algorithm for dynamic balancing of the load in the SDN, and said effect is transmitted to balance the load on the control level of the SDN to the local switching centre (LSC) of the SDN.
EFFECT: increase in the efficiency of use of the bandwidth of a software-defined network (SDN) by making a qualitative transition from an adaptive model of responding to the changes occurring in the network to a proactive model of managing the network as a whole.
7 cl, 6 dwg
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Authors
Dates
2022-08-15—Published
2021-06-11—Filed