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ABSTRACTS OF ARTICLES OF THE JOURNAL "INFORMATION TECHNOLOGIES".
No. 8. Vol. 27. 2021

DOI: 10.17587/it.27.419-424

R. T. Humbatov1, Professor, e-mail: tempus_ramiz@inbox.ru, B. G. Ibrahimov2, Professor, e-mail: i.bayram@mail.ru, A. A. Alieva3, Associate Professor, e-mail: almaz40@gmail.com, R. F. Ibrahimov1, Distater, e-mail: i_rufat.f@mail.ru,
1 Institute of Control Systems of the ANAS, Baku, Republic of Azerbaijan,
2 Azerbaijan Technical University, Baku, Republic of Azerbaijan,
3 Mingechevir State University, Baku, Republic of Azerbaijan

Approaches to the Analysis Performance Indicators Multiservice Telecommunication Networks Based on SDN Technology

The quality of functioning multiservice telecommunication networks based on the architectural concept Next Generation Network (NGN) and Future Networks (FN) using modern innovative technologies has been analyzed. Based on the study, a new approach to the construction model for assessing performance indicators multiservice telecommunication networks based on SDN (Software Defined Networking) technologies, taking into account the property self-similarity traffic is proposed. On the basis of the proposed approach, complex indicators MTS were investigated, taking into account the requirement QoS (Quality of Service) and QoE (Quality of Experience). The mathematical apparatus and the results of the study throughput software and hardware complexes, the probabilistic-time characteristics of the network and the management physical resources in the provision multimedia services are presented. Models have been investigated and analytical expressions have been obtained for the assessment complex indicators of the quality offunctioning MTS in the provision multimedia services with the necessary parameters. À numerical analysis is carried out and a graphical dependence of the maximum network throughput on the total number software and hardware systems for a given system load factor is built.
Keywords: performance, throughput, future networks, SDN, quality of service, NFV, efficiency, IMS, heterogeneous resources

P. 419–424

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