The development and study of the methods and algorithms for the classification of data flows of cloud applications in the network of the virtual data center

Abstract

This paper represents the results of the research, which have allowed us to develop a hybrid approach to the processing, classification, and control of traffic routes. The approach enables to identify traffic flows in the virtual data center in real-time systems. Our solution is based on the methods of data mining and machine learning, which enable to classify traffic more accurately according to more criteria and parameters. As a practical result, the paper represents the algorithmic solution of the classification of the traffic flows of cloud applications and services embodied in a module for the controller of the software-defined network. This solution enables to increase the efficiency of handling user requests to cloud applications and reduce the response time, which has a positive effect on the quality of service in the network of the virtual data center.