EVALUATION OF SERVICES QUALITY IN IMS

Abstract

The main stages of the historical development of telecommunication networks are shown. It is noted that today the most common concepts are NGN (Next Generation Network), supporting the functionality of Triple-Play Services (triple services – voice, video and data transmission), as well as IMS (IP Multimedia Subsystem), which combines cellular technology and landline communications. They are able to provide a wide range of services: basic, additional, intelligent. In addition, IMS is able to provide mobile services. The IMS architecture layers are presented – transport layer, control layer; layer of service and application servers. Particular attention is paid to the layer of service and application servers. Based on the analysis of ITU recommendations, the main telecommunication services quality indexes are determined, namely, the time of service provision, the length of the queue that the service request falls into to wait for service on the server, and the probability of refusing to provide services. Based on the proposed mathematical models of the NGN intelligent superstructure, analytical expressions are presented for calculating the quality indexes of intelligent services in NGN for one type of service and for K types of services, taking into account the self-similarity of traffic, and without taking into account. To evaluate the quality of services in IMS, it is proposed to use the approaches of queuing theory and tensor analysis. Tensor analysis offers a mathematical apparatus for transforming coordinate systems, considering IMS as a set of geometric objects whose projections are different in different coordinate systems, but the physical properties of the objects themselves do not change. Expressions are proposed that make it possible to calculate the following QoS indexes in IMS: average queue length, average residence time of an application in the system for all types of services in IMS. It is considered that the incoming traffic is the simplest. Further development of the work is to take into account the self-similar nature of traffic, which is created by the flow of requests for services that come to IMS, as well as the limitations of the server buffer, which will allow a more accurate assessment of the quality of services in IMS.