Analyzing Traffic Identification Methods for Resource Management in SDN

Abstract

The article is devoted to the analysis of traffic classification methods in SDN network. The review of analytical approaches of traffic identification to identify the solutions used in them, as well as assessing their applicability in the SDN network. Types of machine learning are considered and input parameters are analyzed. The methods of intelligent analysis covered in the scientific articles are systematized according to the following criteria: traffic identification parameters, neural network model, identification accuracy. Based on the analysis of the review results, the conclusion is made about the possibility of applying the considered solutions, as well as the need to form a scheme of SDN network with a module of artificial intelligence elements for load balancing.