OVERLOAD AND TRAFFIC MANAGEMENT OF MESSAGE SOURCES WITH DIFFERENT PRIORITY OF SERVICE
Valerii Kozlovskyi
National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute” (Ukraine)
https://orcid.org/0000-0003-0234-415X
Valerii Kozlovskyi
National Aviation University, Faculty of Cyber Security and Software Engineering, Department of Information Protection System, Kyiv, Ukraine (Ukraine)
https://orcid.org/0000-0002-8301-5501
Andrii Toroshanko
National Aviation University, Faculty of Cyber Security and Software Engineering, Department of Information Protection System, Kyiv, Ukraine (Ukraine)
https://orcid.org/0000-0002-0816-657X
Oleksandr Toroshanko
toroshanko@gmail.comTaras Shevchenko National University of Kyiv (Ukraine)
http://orcid.org/0000-0002-2354-0187
Natalia Yakumchuk
Lutsk National Technical University (Ukraine)
https://orcid.org/0000-0002-8173-449X
Abstract
The scheme of dynamic management of traffic and activity of message sources with different priority of service is considered. The scheme is built on the basis of the neuroprognostic analysis model and the gradient descent method. For prediction and early detection of overload, the apparatus of the general theory of sensitivity with indirect feedback and control of activity of message sources is used. The control algorithm is started at the bottleneck of the network node. It uses a recursive prediction approach where the neural network output is referred to as many steps as defined by a given prediction horizon. Traffic with a higher priority is served without delay using the entire available bandwidth. Low-priority traffic will use the remaining bandwidth not used by higher-priority traffic. An algorithm for estimating the maximum available bandwidth of a communication node for traffic with a low service priority has been developed. This approach makes it possible to improve the efficiency of channel use without affecting the quality of service for high-priority traffic.
Keywords:
telecommunication network, overload prediction, sensitivity function, neural network, gradient descent method, service priorityReferences
Bonaventure O.: Computer Networking: Principles, Protocols and Practices. Release. 2018.
Google Scholar
Golmohammadi A.: Prioritizing Service Quality Dimensions: A Neural Network Approach. World Academy of Science, Engineering & Technology 42, 2010, 602–605.
Google Scholar
Göransson P. et al.: Software Defined Networks: A Comprehensive Approach, 2nd ed. Morgan Kaufmann, 2017.
Google Scholar
Klymash M. M., Strykhaliuk B. M., Kaidan M. V.: Teoreticheskiye osnovy telekommunikatsionnykh setyei. LAP LAMBERT Academic Publishing, Saarbrücken 2014.
Google Scholar
Korolkova A. V., Kulyabov D. S., Tchernoivanov A. I.: On the Classification of RED Algorithms. Bulletin of the Russian Peoples' Friendship University 3, 2009, 34–46.
Google Scholar
Kurose J. F., Keith W. R.: Computer Networking: A Top-Down Approach, 7th Ed. Pearson Education, Inc., 2017.
Google Scholar
Lu Z. et al.: Overload Control for Signaling Congestion of Machine Type Communications in 3GPP Networks. PLOS ONE, 2016. [http://doi.org/10.1371/journal.pone.0167380].
DOI: https://doi.org/10.1371/journal.pone.0167380
Google Scholar
Maximov V. V., Chmykhun S. O.: Classification of algorithms of controlling networks congestions. Scientific proceeding of Ukrainian Research Institute of Communication 5(33), 2014, 73–79.
Google Scholar
Maxymov V. V., Chmykhun S. O.: Research of the algorithm of controlling congestion TCP Veno. Telecommunication and Information Technologies 4, 2015, 30–36.
Google Scholar
Shooman M. L.: Reliability of Computer Systems and Networks – Fault Tolerance, Analysis, Design. JohnWiley&Sons, Inc., NewYork 2002.
DOI: https://doi.org/10.1002/047122460X
Google Scholar
Snarskyy A. A., Lande D. V.: Modelyrovanye slozhnыkh setey. Kyiv 2015.
Google Scholar
Stallings W.: Foundations of Modern Networking: SDN, NFV, QoE, IoT, and Cloud. Pearson Education, Inc., Old Tappan, New Jersey 2016.
Google Scholar
Tanenbaum A. S., Wetherall D. J.: Computer Networks. Prentice Hall, Cloth, 2011.
Google Scholar
Tasad R., Ruggieri M.: Technology Trends in Wireless Communications. Artech House, Boston – London 2003.
Google Scholar
Tkachuk A. et al.: Basic Stations Work Optimization in Cellular Communication Network. D. Cagánová et al. (eds.), Advances in Industrial Internet of Things, Engineering and Management, EAI. Springer Innovations in Communication and Computing, 2021, 1–19.
DOI: https://doi.org/10.1007/978-3-030-69705-1_1
Google Scholar
Toroshanko O. S.: Multi-step model for prognostication and detection of telecommunication network overload. Telecommunication and Information Technologies 2(63), 2019, 35–43.
Google Scholar
Toroshanko Ya. I.: Sensitivity analysis of systems of mass service on the base of model of adaptation and regulation of foreign traffic. Herald of Khmelnytskyi national university 6(243), 2016, 171–175.
Google Scholar
Vinogradov N. et al.: Development of the Method to Control Telecommunication Network Congestion Based on a Neural Model. Eastern-European Journal of Enterprise Technologies 2(9), 2019, 67–73.
DOI: https://doi.org/10.15587/1729-4061.2019.164087
Google Scholar
Vynohradov N. A., Drovovozov V. Y., Lesnaya N. N., Zembytskaya A. S.: Analyz nahruzky na sety peredachy dannыkh v systemakh krytychnoho prymenenyya. Zvyazok 1(61), 2006, 9–12.
Google Scholar
Authors
Valerii KozlovskyiNational Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute” Ukraine
https://orcid.org/0000-0003-0234-415X
Authors
Valerii KozlovskyiNational Aviation University, Faculty of Cyber Security and Software Engineering, Department of Information Protection System, Kyiv, Ukraine Ukraine
https://orcid.org/0000-0002-8301-5501
Authors
Andrii ToroshankoNational Aviation University, Faculty of Cyber Security and Software Engineering, Department of Information Protection System, Kyiv, Ukraine Ukraine
https://orcid.org/0000-0002-0816-657X
Authors
Oleksandr Toroshankotoroshanko@gmail.com
Taras Shevchenko National University of Kyiv Ukraine
http://orcid.org/0000-0002-2354-0187
Authors
Natalia YakumchukLutsk National Technical University Ukraine
https://orcid.org/0000-0002-8173-449X
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