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MODERN INFRASTRUCTURE OF COMMUNICATION TECHNOLOGIES IN BUSINESS: MODELING OF THE METHOD OF «LIVING MIGRATION»

In order to meet data and service requirements, network operators are constantly expanding and improving their network infrastructure, resulting in increased capital and operating costs. However, due to intense competition and falling prices, the average income per user does not increase proportionally, which leads to a decrease in return on investment. Thus, to reduce costs and increase revenue, mobile networks need to make the next evolutionary leap towards 5G, which now applies not only to the mobile border, but also to the core network. The 5G micro-operator service architecture must also be developed together with various technologies such as SDN and NFV. SDN abstracts network architecture by separating network management and redirection functions, allowing network management to become directly programmable and the underlying infrastructure to be abstracted for applications and network services. The interaction between SDN and NFV allows the 5G network to abstractly build the system infrastructure and further increase network flexibility. Therefore, the article substantiates the possibility of market commercialization of the use of technologies of live migration of traffic flow, which allows to give the product unique characteristics. The existing approaches to the solution of the problem of load balancing of the network of 5G micro operators are analyzed. A number of advantages of the live migration method have been identified, namely the possibility of its application for the micro operator's network and efficient use of network resources. According to the results of the experiment, it was found that the method of live migration has better values µO_num (68.1% of traffic flow) than the mechanism of MLF (29.8% of traffic flow). It is proved that the mechanism of live migration can determine the priority of the user traffic flow according to the servers in the zone µO, and therefore it is expedient to apply in terms of optimizing the distribution of traffic flow. The proposed method should increase the utilization of network resources and traffic flow efficiency and lead to a higher level of experience quality (QoE) for network users.