Development of a polymodel complex of information systems resource management

Authors

DOI:

https://doi.org/10.15587/1729-4061.2025.335688

Keywords:

artificial intelligence, destabilizing factors, operational levels, indicators, criteria, efficiency, reliability

Abstract

The object of the study is information systems. The research addresses the problem of increasing the accuracy of modeling the functioning processes of information systems. A polymodel complex for resource management in information systems has been developed.

The originality of the research is ensured by:

– a comprehensive description of the functioning processes of various types of information systems through the development of corresponding mathematical expressions, which enhances the accuracy of modeling for subsequent managerial decision-making;

– the inclusion of both static and dynamic processes occurring within information systems, using a hierarchical system of interconnected mathematical models;

– the ability to model either an individual process within an information system or to perform integrated modeling of multiple processes using a single or a set of mathematical models;

– a dynamic description of the process of controlling the trajectory of information systems during their operation through proposed analytical expressions, enabling forecasting of the system’s behavior N steps ahead;

– modeling the process of operations management during computational tasks within the functioning of information systems, which allows for planning of optimal load distribution on the hardware components;

– simulation of the dynamics of resource management in information systems during their operation, making it possible to forecast the engagement of resources throughout their lifecycle.

The proposed polymodel complex is advisable to use for solving management tasks of information systems characterized by a high level of complexity

Author Biographies

Andrii Shyshatskyi, State University “Kyiv Aviation Institute”

Doctor of Technical Sciences, Senior Researcher, Professor

Department of Intelligent Cybernetic Systems

Ganna Plekhova, Kharkiv National Automobile and Highway University

PhD, Associate Professor, Head of Department

Department of Computer Science and Information Systems

Elena Odarushchenko, Poltava State Agrarian University

PhD, Associate Professor

Department of Information Systems and Technologies

Hennadii Miahkykh, National Defence University of Ukraine

Adjunct

Institute of Information and Communication Technologies and Cyber Defense

Olena Feoktystova, National Aerospace University «Kharkiv Aviation Institute»

PhD, Associate Professor

Department of Software Engineering

Igor Shostak, National Aerospace University «Kharkiv Aviation Institute»

Doctor of Technical Sciences, Professor

Department of Software Engineering

Dmytro Honcharuk, National Defense University of Ukraine

Head of Research Laboratory

Laboratory of Informatization Project Management Problems

Center for Military and Strategic Studies

Oleksandr Lytvynenko, Military Institute of Taras Shevchenko National University of Kyiv

PhD, Senior Researcher

Research Department

Research Center

Anna Lyashenko, Kruty Heroes Military Institute of Telecommunications and Information Technology

Senior Researcher

Scientific Center

Yevhenii Kapran, Kruty Heroes Military Institute of Telecommunications and Information Technology

Adjunct

Scientific and organizational department

References

  1. Sova, O., Radzivilov, H., Shyshatskyi, A., Shvets, P., Tkachenko, V., Nevhad, S. et al. (2022). Development of a method to improve the reliability of assessing the condition of the monitoring object in special-purpose information systems. Eastern-European Journal of Enterprise Technologies, 2 (3 (116)), 6–14. https://doi.org/10.15587/1729-4061.2022.254122
  2. Dudnyk, V., Sinenko, Y., Matsyk, M., Demchenko, Y., Zhyvotovskyi, R., Repilo, I. et al. (2020). Development of a method for training artificial neural networks for intelligent decision support systems. Eastern-European Journal of Enterprise Technologies, 3 (2 (105)), 37–47. https://doi.org/10.15587/1729-4061.2020.203301
  3. Sova, O., Shyshatskyi, A., Salnikova, O., Zhuk, O., Trotsko, O., Hrokholskyi, Y. (2021). Development of a method for assessment and forecasting of the radio electronic environment. EUREKA: Physics and Engineering, 4, 30–40. https://doi.org/10.21303/2461-4262.2021.001940
  4. Kuchuk, N., Merlak, V., Skorodelov, V. (2020). A method of reducing access time to poorly structured data. Advanced Information Systems, 4 (1), 97–102. https://doi.org/10.20998/2522-9052.2020.1.14
  5. Meleshko, Y., Drieiev, O., Drieieva, H. (2020). Method of identification bot profiles based on neural networks in recommendation systems. Advanced Information Systems, 4 (2), 24–28. https://doi.org/10.20998/2522-9052.2020.2.05
  6. Wang, J., Neil, M., Fenton, N. (2020). A Bayesian network approach for cybersecurity risk assessment implementing and extending the FAIR model. Computers & Security, 89, 101659. https://doi.org/10.1016/j.cose.2019.101659
  7. Matheu-García, S. N., Hernández-Ramos, J. L., Skarmeta, A. F., Baldini, G. (2019). Risk-based automated assessment and testing for the cybersecurity certification and labelling of IoT devices. Computer Standards & Interfaces, 62, 64–83. https://doi.org/10.1016/j.csi.2018.08.003
  8. Henriques de Gusmão, A. P., Mendonça Silva, M., Poleto, T., Camara e Silva, L., Cabral Seixas Costa, A. P. (2018). Cybersecurity risk analysis model using fault tree analysis and fuzzy decision theory. International Journal of Information Management, 43, 248–260. https://doi.org/10.1016/j.ijinfomgt.2018.08.008
  9. Folorunso, O., Mustapha, O. A. (2015). A fuzzy expert system to Trust-Based Access Control in crowdsourcing environments. Applied Computing and Informatics, 11 (2), 116–129. https://doi.org/10.1016/j.aci.2014.07.001
  10. Mohammad, A. (2020). Development of the concept of electronic government construction in the conditions of synergetic threats. Technology Audit and Production Reserves, 3 (2 (53)), 42–46. https://doi.org/10.15587/2706-5448.2020.207066
  11. Bodin, L. D., Gordon, L. A., Loeb, M. P., Wang, A. (2018). Cybersecurity insurance and risk-sharing. Journal of Accounting and Public Policy, 37 (6), 527–544. https://doi.org/10.1016/j.jaccpubpol.2018.10.004
  12. Cormier, A., Ng, C. (2020). Integrating cybersecurity in hazard and risk analyses. Journal of Loss Prevention in the Process Industries, 64, 104044. https://doi.org/10.1016/j.jlp.2020.104044
  13. Hoffmann, R., Napiórkowski, J., Protasowicki, T., Stanik, J. (2020). Risk based approach in scope of cybersecurity threats and requirements. Procedia Manufacturing, 44, 655–662. https://doi.org/10.1016/j.promfg.2020.02.243
  14. Perrine, K. A., Levin, M. W., Yahia, C. N., Duell, M., Boyles, S. D. (2019). Implications of traffic signal cybersecurity on potential deliberate traffic disruptions. Transportation Research Part A: Policy and Practice, 120, 58–70. https://doi.org/10.1016/j.tra.2018.12.009
  15. Promyslov, V. G., Semenkov, K. V., Shumov, A. S. (2019). A Clustering Method of Asset Cybersecurity Classification. IFAC-PapersOnLine, 52 (13), 928–933. https://doi.org/10.1016/j.ifacol.2019.11.313
  16. Zarreh, A., Saygin, C., Wan, H., Lee, Y., Bracho, A. (2018). A game theory based cybersecurity assessment model for advanced manufacturing systems. Procedia Manufacturing, 26, 1255–1264. https://doi.org/10.1016/j.promfg.2018.07.162
  17. Kosko, B. (1986). Fuzzy cognitive maps. International Journal of Man-Machine Studies, 24 (1), 65–75. https://doi.org/10.1016/s0020-7373(86)80040-2
  18. Levashenko, V., Liashenko, O., Kuchuk, H. (2020). Building Decision Support Systems based on Fuzzy Data. Advanced Information Systems, 4 (4), 48–56. https://doi.org/10.20998/2522-9052.2020.4.07
  19. Kashkevich, S. (Ed.) (2025). Decision support systems: mathematical support. Kharkiv: TECHNOLOGY CENTER PC. https://doi.org/10.15587/978-617-8360-13-9
  20. Shyshatskyi, A. (Ed.) (2024). Information and control systems: modelling and optimizations. Kharkiv: TECHNOLOGY CENTER PC. https://doi.org/10.15587/978-617-8360-04-7
Development of a polymodel complex of information systems resource management

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Published

2025-08-30

How to Cite

Shyshatskyi, A., Plekhova, G., Odarushchenko, E., Miahkykh, H., Feoktystova, O., Shostak, I., Honcharuk, D., Lytvynenko, O., Lyashenko, A., & Kapran, Y. (2025). Development of a polymodel complex of information systems resource management. Eastern-European Journal of Enterprise Technologies, 4(4 (136), 58–72. https://doi.org/10.15587/1729-4061.2025.335688

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Section

Mathematics and Cybernetics - applied aspects