The traffic distribution model of the multilevel infocommunication network of special-use.

Infocommunication networks provide the base structure for analysis, processing and transmission of information. Main principles networking and infocommunication networks technologies is independent from type of destination. Therefore, infocommunication networks can be used for dual-use (civil and military purposes). In any case, traffic distribution analysis of infocommunication networks allows to estimate a quality of service of information streams for providing such properties of special-use infocommunication networks as: timeliness of information delivery, promptness, sustainability and continuity of communication. Application of different types of modelling to traffic distribution analysis provides ample opportunities for estimation of infocommunication networks projects under development that it increases the level of practical feasibility of these projects. In this work the tensor analysis of networks is used for modelling of traffic distribution in special-use infocommunication network. The investigated object is the multilevel infocommunication network with several levels: the level of gathering information, the aggregation level, the level of preliminary processing, the level of information centers. The mesh and node tensor models are used for the estimation of mean delay of networks routes. The joint application of two methods of tensor modelling allows to formalize the process of estimation mean delay for set of network routes. In result, the routes with maximal mean delay were determined for infocommunication network of special-use and the conclusion was made about necessity of optimization of traffic distribution to reduce time delay.

1. Makarenko S.I. Descriptive Model of Special Communication Network. Systems of Control, Communication and Security. 2017;2:113–164. DOI: 10.24411/2410-9916-2017-10205.

2. Pylinsky M.V., Krivtsov S.P., Zakharchenko A.S. Hierarchical system of performance indicators for the operation of a special purpose communication networks as a multi-level and dynamic system. Scientific and Technical Journal. Counter-terrorism technical devices. Issue 16. 2020;3-4(141-142):103-110.

3. Konoshenko S.A., Kretov A.A., Dudukin A.S. Adaptive routing of application flows in a multiservice communication network. Scientific and Technical Journal. Counter-terrorism technical devices. Issue 16. 2020;1-2(139-140):68-71.

4. Legkov K.E. A mathematical model of the infocommunication system of special purpose. H&ES Research. 2016;8(2):6–14.

5. Pylinskii M.V. The details of modeling of communication networks of special purpose. Izvestiya TulGU. Technical sciences. 2018;10:483–490.

6. Ponomarev D.Yu. Tenzornaya metodologiya v informatsionnykh kommunikatsiyakh. Izvestiya vysshikh uchebnykh zavedeniy. Priborostroenie. 2012;55(5):18-23.

7. Ponomarev D. Features of application of tensor analysis to telecommunication networks modelling. Modeling, Optimization and Information Technology. 2018;6(2):46-63.

8. Petrov A.E. Tenzornyy metod dvoystvennykh setey. 2007.

9. Ponomarev D. Issledovanie veroyatnostno-vremennykh kharakteristik setei massovogo obsluzhivaniya konturnym metodom tenzornogo analiza. FIPS (Rospatent): Svidetel'stvo o gosudarstvennoi registratsii programmy dlya EVM. 07.10.2010;2010616674.

10. Ponomarev D. Issledovanie veroyatnostno-vremennykh kharakteristik IP setei uzlovym metodom tenzornogo analiza. FIPS (Rospatent): Svidetel'stvo o gosudarstvennoi registratsii programmy dlya EVM. 25.09.2009;2009615358.