Neural network model for optimize network work in the infrastructure of the virtual data center

Abstract

The paper describes an approach to development a neural network model for identification virtual network functions. Our solution are based on the analysis the statistical properties of flows circulating in the network of the virtual data center and characteristics that describe the content of packets transmitted through network objects. This enabled us to establish the optimal set of attributes to identify virtual network functions. We developed an algorithm for optimizing the placement of virtual data functions using the data obtained in our research. The approach applied in our investigation for placement of virtual network functions allows to optimizing traffic flows in virtual data center. The algorithmic solution is based on neural networks, which enables to scale it at any number of the network function copies.