SYNERGETIC APPROACH TO THE STUDY OF CONTROL SYSTEMS
DOI:
https://doi.org/10.37943/AITU.2020.68.59.004Keywords:
Control system, Software Defined Network, SDN, optimization, system stability, synergetic control, synergetic, attractor.Abstract
The paper considers a new direction of scientific research – «synergetics». The key provisions and its development as a science are considered. The focus is on open feedback systems as objects of research. The properties of these systems – openness, nonlinearity, dissipation and multidimensionality, allow the use of a synergistic approach in the study. Due to new trends in information technology in recent years, interest in the new architecture of Software Defined Networks has grown. A programmable controller is used as a control mechanism for SDN networks. The connection between the logical controller and the physical network is made using the OpenFlow protocol. The graph of the network topology is presented as a set of key parameters that come to the controller. From the set of parameters, the key ones used in the study are selected. The dynamics of the ratio of key parameters under the condition of optimizing the network infrastructure is studied. The dynamics of the network corresponding to the stability condition is investigated by the methods of synergetic control theory. SDN network control is formed by methods based on the principle of self-organization of nonlinear systems. As a result, synergetic control is synthesized to increase the resistance of the control system to destructive influences. Based on the selected dynamic invariant, the possibility of providing the selection of the parameter of the SDN network management system for the transition to a controlled state is shown.
References
Haken, H. (1983). Synergetics, an Introduction: Nonequilibrium Phase Transitions and Self-Organization in Physics, Chemistry, and Biology", (3rd ed.). New-York: Springer-Verlag.
Kolesnikov, A. A. (2005). Sinergeticheskoe metody upravlenija slozhnymi sistemami: teorija sistemnogo sinteza. Moscow, URSS, 228.
Prigozhin, I., & Stengers, I., Arshinova V. I., Klimontovicha, Ju. L., & Sachkova, Ju. V. (1984). Porjadok iz haosa: Novyj dialog cheloveka s prirodoj [per. s angl.]. Moscow, Nauka, 432.
Barabash, O., Kravchenko, Y., Mukhin, V., Kornaga, Y., & Leshchenko, O. (2017). Optimization of Parameters at SDN Technologie Networks. International Journal of Intelligent Systems and Applications, 9(9), 1–9. https://doi.org/10.5815/ijisa.2017.09.01
Toliupa, S., Babenko, T., & Trush, A. (2017). The building of a security strategy based on the model of game management. 2017 4th International Scientific-Practical Conference Problems of Infocommunications. Science and Technology (PIC S&T). Kharkov, 57 – 60. https://doi: 10.1109/INFOCOMMST.2017.8246349.
Korotin, S., Kravchenko, Y., Starkova, O., Herasymenko, K., & Mykolaichuk, R. (2019) Analytical determination of the parameters of the self-tuning circuit of the traffic control system on the limit of vibrational stability. IEEE International Scientific-Practical Conference Problems of Infocommunications Science and Technology, PIC S&T'2019 Proceedings, 471–476.
Rakushev, M., Kovbasiuk, S., Kravchenko, Y., & Pliushch, O. (2017). Robustness evaluation of differential spectrum of integration computational algorithms. 2017 4th International Scientific-Practical Conference Problems of Infocommunications. Science and Technology (PIC S&T). Kharkov, 21 – 24. https://doi: 10.1109/INFOCOMMST.2017. 8246140.
Zhenbing, H., Mukhin, V., Kornaga, Y., Herasymenko, O., & Bazaka, Y. (2017). The scheduler for the gridsystem based on the parameters monitoring of the computer components. Eastern-European Journal of Enterprise Technologies, 1(2–85), 31–39. https://doi.org/10.15587/1729-4061.2017.91271
Barabash, O., Dakhno, N., Shevchenko, H., & Sobchuk, V. (2019). Unmanned Aerial Vehicles Flight Trajectory Optimisation on the Basis of Variational Enequality Algorithm and Projection Method. 2019 IEEE 5th International Conference Actual Problems of Unmanned Aerial Vehicles Developments (APUAVD). Kiev, Ukraine, 136–139. https://doi: 10.1109/APUAVD47061.2019.8943869.
Barabash, O.V., Dakhno, N.B., Shevchenko, H.V., & Sobchuk V.V. (2018). Integro-Differential Models of Decision Support Systems for Controlling Unmanned Aerial Vehicles on the Basis of Modified Gradient Method. 2018 IEEE 5th International Conference on Methods and Systems of Navigation and Motion Control (MSNMC). Kyiv, 94 – 97. https://doi: 10.1109/MSNMC.2018.8576310.
Hu, Z., Mukhin, V., Kornaga, Y., Volokyta, A., & Herasymenko, O. (2017). The scheduler for distributed computer systems based on the network centric approach to resources control. In Proceedings of the 2017 IEEE 9th International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications, IDAACS 2017, 1. 518–523. Institute of Electrical and Electronics Engineers Inc. https://doi.org/10.1109/IDAACS.2017.8095135.
Kravchenko, Y., Leshchenko, O., Trush, O., Makhovych, O., Dakhno, N. (2019). Evaluating the effectiveness of cloud services. 2019 IEEE 1th International Scientific-Practical Conference Problems of Infocommunications Science and Technology, PIC S&T`2019. Kyiv, 120–124.
Leshchenko, O., & Trush, O. (2018). Criteria for evaluating the efficiency of wireless sensor networks. International Scientific and Practical Conference . Cybersecurity Issues of Information and Telecommunication Systems (PCSITS), Kyiv, 76-89.
Kravchenko, Y., Starkova, O., Herasymenko, K., & Kharchenko, A. (2017). Technology analysis for smart home implementation," 2017 4th International Scientific-Practical Conference Problems of Infocommunications. Science and Technology (PIC S&T), Kharkov, 579-584.
Kovtun, O., Pleskach V., & Tkalich O. (2016). Wireless of network whith the use of standards ZIGBEE, BLUETOOTH, WI-FI. Radioelectronic and computer systems, 4, 42-47.
Dukhnovska, K. (2016). Formuvannya Posukovy dynamical vector space “Shtunniy intertekt”. (3)4.
Barabash, O.V., Open’ko, P.V., Kopiika, O.V., Shevchenko, H.V., & Dakhno N.B. (2019). Target Programming with Multicriterial Restrictions Application to the Defense Budget Optimization. Advances in Military Technology, 4(2), 213 – 229. ISSN 1802-2308, eISSN 2533-4123. http://doi:10.3849/aimt.0129, http://aimt.unob.cz/articles/19_02/1291.pdf.
Toliupa, S., Tereikovskiy, I., Dychka, I., Tereikovska, L., & Trush A. (2019). The Method of Using Production Rules in Neural Network Recognition of Emotions by Facial Geometry. 2019 3rd International Conference on Advanced Information and Communications Technologies (AICT). Lviv, Ukraine, 323-327. http://doi: 10.1109/AIACT.2019.8847847.
Cai, L., Chen, D., & Zhang, L. (2017). A Strategy of Dynamic Routing Based on SDN. Infinite Study.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2023 Articles are open access under the Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Authors who publish a manuscript in this journal agree to the following terms:
- The authors reserve the right to authorship of their work and transfer to the journal the right of first publication under the terms of the Creative Commons Attribution License, which allows others to freely distribute the published work with a mandatory link to the the original work and the first publication of the work in this journal.
- Authors have the right to conclude independent additional agreements that relate to the non-exclusive distribution of the work in the form in which it was published by this journal (for example, to post the work in the electronic repository of the institution or publish as part of a monograph), providing the link to the first publication of the work in this journal.
- Other terms stated in the Copyright Agreement.