Improvement of complex resource management of special-purpose communication systems

Authors

DOI:

https://doi.org/10.15587/1729-4061.2022.266009

Keywords:

special-purpose communication system, destabilizing factors, communication system resources, communication system topology

Abstract

The object of the research is a special-purpose communication system. The relevance of the research lies in the need for complex management of resources of special-purpose communication systems. The resources of the special-purpose communication system are defined as: spatial, temporal, frequency and hardware resources. Destabilizing factors include: intentional interference; denial-of-service cyber attacks and fire damage to individual elements of the special-purpose communication system. The method of complex management of resources of special-purpose communication systems was improved. The difference between the proposed method and the known ones is that the specified method contains improved procedures:

‒ determination of the impact of destabilizing factors on the special-purpose communication system;

‒ description of special-purpose communication systems of various architectures;

‒ determination of the rational route of information transmission and operation mode of communication devices in the general special-purpose communication system;

‒ consideration of uncertainty about the state of the special-purpose communication system;

‒ determination of the number of necessary forces and means of communication, which must be increased for the full functioning of the special communication system. The improved method provides a gain of 20‒26 % compared to classical approaches to the management of resources of special-purpose communication systems. The improved method can be used at the control points of the communication system of groups of troops (forces) while planning the organization of communication and at the stage of operational management of the communication system.

Author Biographies

Mykhailo Koval, The National Defence University of Ukraine named after Ivan Cherniakhovskyi

Doctor of Military Sciences, Head of University

Oleg Sova, Military Institute of Telecommunications and Information Technologies named after Heroes of Kruty

Doctor of Technical Sciences, Senior Researcher, Head of Department

Department of Automated Control Systems

Oleksandr Orlov, V. N. Karazin Kharkiv National University

Doctor of Sciences in Public Administration, Professor, Head of Department

Department of Digital Technologies and Electronic Government

Educational and Scientific Institute "Institute of Public Administration"

Andrii Shyshatskyi, Research Center for Trophy And Perspective Weapons and Military Equipment

PhD, Senior Researcher, Head of Department

Department of Robotic Systems Research

Yurii Artabaiev, Research Center for Trophy And Perspective Weapons and Military Equipment

PhD, Head of Department

Research Department of Combat Crews

Oleh Shknai, Military Unit A1906

PhD, Leading Researcher

Research Department

Andrii Veretnov, Central Scientifically-Research Institute of Armaments and Military Equipment of the Armed Forces of Ukraine

PhD, Leading Researcher

Research Department

Oleksandr Koshlan, The National Defence University of Ukraine named after Ivan Cherniakhovskyi

PhD, Head of Department

Scientific Department of General and Resource Planning

Yevhen Zhyvylo, The National Defence University of Ukraine named after Ivan Cherniakhovskyi

PhD, Head of Department

Department of Communications and Automated Troop Management Systems

Iryna Zhyvylo, National Scientific Center "M.D. Strazhesko Institute of Cardiology"

PhD, Junior Researcher

References

  1. Bashkyrov, O. M., Kostyna, O. M., Shyshatskyi, A. V. (2015). Rozvytok intehrovanykh system zviazku ta peredachi danykh dlia potreb Zbroinykh Syl. Ozbroiennia ta viiskova tekhnika, 1 (5), 35–40. Available at: http://nbuv.gov.ua/UJRN/ovt_2015_1_7
  2. Kalantaievska, S., Pievtsov, H., Kuvshynov, O., Shyshatskyi, A., Yarosh, S., Gatsenko, S. et. al. (2018). Method of integral estimation of channel state in the multiantenna radio communication systems. Eastern-European Journal of Enterprise Technologies, 5 (9 (95)), 60–76. doi: https://doi.org/10.15587/1729-4061.2018.144085
  3. Kuchuk, N., Mohammed, A. S., Shyshatskyi, A., Nalapko, O. (2019). The method of improving the efficiency of routes selection in networks of connection with the possibility of self-organization. International Journal of Advanced Trends in Computer Science and Engineering, 8 (1.2). Available at: http://repository.kpi.kharkov.ua/bitstream/KhPI-Press/51500/1/IJATCSE_2019_8_1_2_Kuchuk_The_method.pdf
  4. Sliusar, V. I., Zinchenko, A. O., Zinchenko, K. A. (2015). Systema mobilnoho zviazku standartu GSM dlia potreb radiolokatsiinoho kontroliu povitrianoho prostoru. Suchasni informatsiyni tekhnolohiyi u sferi bezpeky ta oborony, 2 (23), 108–114.
  5. Sliusar, I. I., Sliusar, V. I., Smoliar, V. H., Omarov, M. I., Khomenko, R. V. (2016). Shliakhy udoskonalennia system trankinhovoho zviazku Ukrainy. Novitni informatsiyni systemy ta tekhnolohiyi, 5, 36–47.
  6. Jalil Piran, M., Pham, Q.-V., Islam, S. M. R., Cho, S., Bae, B., Suh, D. Y., Han, Z. (2020). Multimedia communication over cognitive radio networks from QoS/QoE perspective: A comprehensive survey. Journal of Network and Computer Applications, 172, 102759. doi: https://doi.org/10.1016/j.jnca.2020.102759
  7. Khan, M. W., Zeeshan, M. (2019). QoS-based dynamic channel selection algorithm for cognitive radio based smart grid communication network. Ad Hoc Networks, 87, 61–75. doi: https://doi.org/10.1016/j.adhoc.2018.11.007
  8. Majumder, T., Mishra, R. K., Singh, S. S., Sahu, P. K. (2020). Robust congestion control in cognitive radio network using event-triggered sliding mode based on reaching laws. Journal of the Franklin Institute, 357 (11), 7399–7422. doi: https://doi.org/10.1016/j.jfranklin.2020.05.019
  9. Lin, Y.-C., Shih, Z.-S. (2018). Design and simulation of a radio spectrum monitoring system with a software-defined network. Computers & Electrical Engineering, 68, 271–285. doi: https://doi.org/10.1016/j.compeleceng.2018.03.043
  10. Rharras, A. E., Saber, M., Chehri, A., Saadane, R., Hakem, N., Jeon, G. (2020). Optimization of Spectrum Utilization Parameters in Cognitive Radio Using Genetic Algorithm. Procedia Computer Science, 176, 2466–2475. doi: https://doi.org/10.1016/j.procs.2020.09.328
  11. Tanergüçlü, T., Karaşan, O. E., Akgün, İ., Karaşan, E. (2019). Radio Communications Interdiction Problem under deterministic and probabilistic jamming. Computers & Operations Research, 107, 200–217. doi: https://doi.org/10.1016/j.cor.2019.03.013
  12. Kumar, S., Singh, A. K. (2021). A localized algorithm for clustering in cognitive radio networks. Journal of King Saud University - Computer and Information Sciences, 33 (5), 600–607. doi: https://doi.org/10.1016/j.jksuci.2018.04.004
  13. Kaur, A., Kumar, K. (2020). Intelligent spectrum management based on reinforcement learning schemes in cooperative cognitive radio networks. Physical Communication, 43, 101226. doi: https://doi.org/10.1016/j.phycom.2020.101226
  14. Onumanyi, A. J., Abu-Mahfouz, A. M., Hancke, G. P. (2021). Amplitude quantization method for autonomous threshold estimation in self-reconfigurable cognitive radio systems. Physical Communication, 44, 101256. doi: https://doi.org/10.1016/j.phycom.2020.101256
  15. Bodyanskiy, E., Strukov, V., Uzlov, D. (2017). Generalized metrics in the problem of analysis of multidimensional data with different scales. Zbirnyk naukovykh prats Kharkivskoho universytetu Povitrianykh Syl, 3 (52), 98–101. Available at: http://nbuv.gov.ua/UJRN/ZKhUPS_2017_3_22
  16. Tymchuk, S. (2017). Methods of Complex Data Processing from Technical Means of Monitoring. Path of Science, 3 (3), 4.1-4.9. doi: https://doi.org/10.22178/pos.20-4
  17. Shyshatskyi, A., Sova, O., Zhuravskyi, Y., Zhyvotovskyi, R., Lyashenko, A., Cherniak, O. et. al. (2020). Development of resource distribution model of automated control system of special purpose in conditions of insufficiency of information on operational development. Technology Audit and Production Reserves, 1 (2 (51)), 35–39. doi: https://doi.org/10.15587/2312-8372.2020.198082
  18. Koshlan, A., Salnikova, O., Chekhovska, M., Zhyvotovskyi, R., Prokopenko, Y., Hurskyi, T. et. al. (2019). Development of an algorithm for complex processing of geospatial data in the special-purpose geoinformation system in conditions of diversity and uncertainty of data. Eastern-European Journal of Enterprise Technologies, 5 (9 (101)), 35–45. doi: https://doi.org/10.15587/1729-4061.2019.180197
  19. Pievtsov, H., Turinskyi, O., Zhyvotovskyi, R., Sova, O., Zvieriev, O., Lanetskii, B., Shyshatskyi, A. (2020). Development of an advanced method of finding solutions for neuro-fuzzy expert systems of analysis of the radioelectronic situation. EUREKA: Physics and Engineering, 4, 78–89. doi: https://doi.org/10.21303/2461-4262.2020.001353
  20. Zuiev, P., Zhyvotovskyi, R., Zvieriev, O., Hatsenko, S., Kuprii, V., Nakonechnyi, O. et. al. (2020). Development of complex methodology of processing heterogeneous data in intelligent decision support systems. Eastern-European Journal of Enterprise Technologies, 4 (9 (106)), 14–23. doi: https://doi.org/10.15587/1729-4061.2020.208554
  21. Shyshatskyi, A. (2020). Complex Methods of Processing Different Data in Intellectual Systems for Decision Support System. International Journal of Advanced Trends in Computer Science and Engineering, 9 (4), 5583–5590. doi: https://doi.org/10.30534/ijatcse/2020/206942020
  22. Sova, O., Golub, V., Shyshatskyi, A., Ostapchuk, V., Nalapko, O., Zubrytska, H. (2019). Method of Forecasting the Duration of Data Transmission Routes in Mobile Radio Networks. 2019 IEEE 2nd Ukraine Conference on Electrical and Computer Engineering (UKRCON). doi: https://doi.org/10.1109/ukrcon.2019.8879978
  23. Mahdi, Q. A., Shyshatskyi, A., Prokopenko, Y., Ivakhnenko, T., Kupriyenko, D., Golian, V. et. al. (2021). Development of estimation and forecasting method in intelligent decision support systems. Eastern-European Journal of Enterprise Technologies, 3 (9 (111)), 51–62. doi: https://doi.org/10.15587/1729-4061.2021.232718
  24. Makridenko, L. A., Volkov, S. N., Khodnenko, V. P. (2010). Kontseptual'nye voprosy sozdaniya i primeneniya malykh kosmicheskikh apparatov. Voprosy elektromekhaniki, 114, 15–26.
  25. Trotsenko, R. V., Bolotov, M. V. (2014). Data extraction process for heterogeneous sources. Privolzhskiy nauchniy vestnik, 12-1 (40), 52–54.
  26. Lei, Z., Yang, P., Zheng, L. (2018). Detection and Frequency Estimation of Frequency Hopping Spread Spectrum Signals Based on Channelized Modulated Wideband Converters. Electronics, 7 (9), 170. doi: https://doi.org/10.3390/electronics7090170
  27. Kanaa, A., Sha’ameri, A. Z. (2018). A robust parameter estimation of FHSS signals using time–frequency analysis in a non-cooperative environment. Physical Communication, 26, 9–20. doi: https://doi.org/10.1016/j.phycom.2017.10.013
  28. Jin, J., Xie, H., Hu, J., Yin, W.-Y. (2014). Characterization of anti-jamming effect on the Joint Tactical Information Distribution System (JTIDS) operating in complicated electromagnetic environment. 2014 International Symposium on Electromagnetic Compatibility. doi: https://doi.org/10.1109/emceurope.2014.6931048
  29. Liu, F., Marcellin, M. W., Goodman, N. A., Bilgin, A. (2013). Compressive detection of frequency-hopping spread spectrum signals. Compressive Sensing II. doi: https://doi.org/10.1117/12.2015969
  30. Gorokhovatsky, V., Stiahlyk, N., Tsarevska, V. (2021). Combination method of accelerated metric data search in image classification problems. Advanced Information Systems, 5 (3), 5–12. doi: https://doi.org/10.20998/2522-9052.2021.3.01
  31. Levashenko, V., Liashenko, O., Kuchuk, H. (2020). Building Decision Support Systems based on Fuzzy Data. Advanced Information Systems, 4 (4), 48–56. doi: https://doi.org/10.20998/2522-9052.2020.4.07
  32. 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. doi: https://doi.org/10.20998/2522-9052.2020.2.05
  33. Kuchuk, N., Merlak, V., Skorodelov, V. (2020). A method of reducing access time to poorly structured data. Advanced Information Systems, 4 (1), 97–102. doi: https://doi.org/10.20998/2522-9052.2020.1.14
  34. Shyshatskyi, A., Tiurnikov, M., Suhak, S., Bondar, O., Melnyk, A., Bokhno, T., Lyashenko, A. (2020). Method of assessment of the efficiency of the communication of operational troop grouping system. Advanced Information Systems, 4 (1), 107–112. doi: https://doi.org/10.20998/2522-9052.2020.1.16
  35. Raskin, L., Sira, O. (2016). Method of solving fuzzy problems of mathematical programming. Eastern-European Journal of Enterprise Technologies, 5 (4 (83)), 23–28. doi: https://doi.org/10.15587/1729-4061.2016.81292
  36. Lytvyn, V., Vysotska, V., Pukach, P., Brodyak, O., Ugryn, D. (2017). Development of a method for determining the keywords in the slavic language texts based on the technology of web mining. Eastern-European Journal of Enterprise Technologies, 2 (2 (86)), 14–23. doi: https://doi.org/10.15587/1729-4061.2017.98750
  37. Stepanenko, A., Oliinyk, A., Deineha, L., Zaiko, T. (2018). Development of the method for decomposition of superpositions of unknown pulsed signals using the second­order adaptive spectral analysis. Eastern-European Journal of Enterprise Technologies, 2 (9 (92)), 48–54. doi: https://doi.org/10.15587/1729-4061.2018.126578
  38. Gorbenko, I., Ponomar, V. (2017). Examining a possibility to use and the benefits of post-quantum algorithms dependent on the conditions of their application. Eastern-European Journal of Enterprise Technologies, 2 (9 (86)), 21–32. doi: https://doi.org/10.15587/1729-4061.2017.96321
  39. Lovska, A. (2015). Peculiarities of computer modeling of strength of body bearing construction of gondola car during transportation by ferry-bridge. Metallurgical and Mining Industry, 1, 49–54. Available at: https://www.metaljournal.com.ua/assets/Journal/english-edition/MMI_2015_1/10%20Lovska.pdf
  40. Lovska, A., Fomin, O. (2020). A new fastener to ensure the reliability of a passenger car body on a train ferry. Acta Polytechnica, 60 (6). doi: https://doi.org/10.14311/ap.2020.60.0478
Improvement of complex resource management of special-purpose communication systems

Downloads

Published

2022-10-27

How to Cite

Koval, M., Sova, O., Orlov, O., Shyshatskyi, A., Artabaiev, Y., Shknai, O., Veretnov, A., Koshlan, O., Zhyvylo, Y., & Zhyvylo, I. (2022). Improvement of complex resource management of special-purpose communication systems . Eastern-European Journal of Enterprise Technologies, 5(9(119), 34–44. https://doi.org/10.15587/1729-4061.2022.266009

Issue

Vol. 5 No. 9(119) (2022): Information and controlling system

Section

Information and controlling system

License

Copyright (c) 2022 Mykhailo Koval, Oleg Sova, Oleksandr Orlov, Andrii Shyshatskyi, Yurii Artabaiev, Oleh Shknai, Andrii Veretnov, Oleksandr Koshlan, Yevhen Zhyvylo, Iryna Zhyvylo

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

The consolidation and conditions for the transfer of copyright (identification of authorship) is carried out in the License Agreement. In particular, the authors reserve the right to the authorship of their manuscript and transfer the first publication of this work to the journal under the terms of the Creative Commons CC BY license. At the same time, they have the right to conclude on their own additional agreements concerning the non-exclusive distribution of the work in the form in which it was published by this journal, but provided that the link to the first publication of the article in this journal is preserved.

A license agreement is a document in which the author warrants that he/she owns all copyright for the work (manuscript, article, etc.).
The authors, signing the License Agreement with TECHNOLOGY CENTER PC, have all rights to the further use of their work, provided that they link to our edition in which the work was published.
According to the terms of the License Agreement, the Publisher TECHNOLOGY CENTER PC does not take away your copyrights and receives permission from the authors to use and dissemination of the publication through the world's scientific resources (own electronic resources, scientometric databases, repositories, libraries, etc.).
In the absence of a signed License Agreement or in the absence of this agreement of identifiers allowing to identify the identity of the author, the editors have no right to work with the manuscript.
It is important to remember that there is another type of agreement between authors and publishers – when copyright is transferred from the authors to the publisher. In this case, the authors lose ownership of their work and may not use it in any way.