Skip to main content
Log in

Conceptual Model for Adaptive Control of a Geographic Information System under Conditions of Destabilization

  • Published:
Automatic Control and Computer Sciences Aims and scope Submit manuscript

Abstract

A conceptual model for a geographic information system operating under conditions of destabilization is proposed. Destabilizing factors have a deterministic, stochastic, and nonstochastic nature. A geographic information system is considered as a controlled object with a variable structure; a problem of adaptation to destabilization is formulated.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1.
Fig. 2.

Similar content being viewed by others

REFERENCES

  1. Sikarev, I.A., Chistyakov, G.B., Garanin, A.V., and Moskvin, D.A., Algorithms for enhancing information security in the processing of navigation data of unmanned vessels of the technical fleet of the inland waterways of the Russian Federation, Autom. Control Comput. Sci., 2020, vol. 54, no. 8, pp. 962–965.  https://doi.org/10.3103/S0146411620080325

    Article  Google Scholar 

  2. Burlov, V.G., Gryzunov, V.V., and Tatarnikova, T.M., Threats of information security in the application of GIS in the interests of the digital economy, J. Phys.: Conf. Ser., 2020, vol. 1703, p. 012023.  https://doi.org/10.1088/1742-6596/1703/1/012023

    Article  Google Scholar 

  3. Kalinin, V.N., Teoreticheskie osnovy sistemnykh issledovanii: kratkii avtorskii kurs lektsiya dlya ad”yunktov akademii (Theoretical Foundations of Systems Research: Brief Lecture Notes for Academy Service Students), St. Petersburg: Voen. Kosmich. Akad. Mozhaiskogo, 2011.

  4. GOST R 52438-2005: Geographical Information Systems. Terms and Definitions, 2018.

  5. Gryzunov, V.V., Model of purpose aggressive actions on the information-computing system, in Chelovecheskii faktor v slozhnykh tekhnicheskikh sistemakh i sredakh (Ergo-2018) (Human Factor in Complex Technical Systems and Environments (Ergo-2018)), Anokhin, A.N., Oboznov, A.A., Paderno, P.I., and Sergeev, S.F., Eds., St. Petersburg: Ergonomicheskaya Assotsiatsiya, 2018.

  6. Bibashov, S.A., The model of formation the requirements for information security to the developed automated systems in the protected execution, Vopr. Kiberbezop., 2017, no. 5, pp. 83–90. https://doi.org/10.21681/2311-3456-2017-5-83-90

  7. Rastrigin, L.A., Adaptatsiya slozhnykh sistem (Adaptation of Complex Systems), Riga: Zinatne, 1981.

  8. Sakharov, V.V., Sikarev, I.A., and Chertkov, A.A., Automating search optimal routes and goods flows in transport networks by means of the integer linear programming, Vestn. Gos. Univ. Morskogo Rechnogo Flota Adm. Makarova, 2018, vol. 10, no. 3, pp. 647–657.  https://doi.org/10.21821/2309-5180-2018-10-3-647-657

    Article  Google Scholar 

  9. Kalinin, M. Zegzhda, P. Zegzhda, D., Vasiliev, Yu., and Belenko, V., Software defined security for vehicular ad hoc networks, Int. Conf. on Information and Communication Technology Convergence (ICTC), Jeju, Korea, 2016, IEEE, 2016, pp. 533–537.  https://doi.org/10.1109/ICTC.2016.7763528

  10. Burlov, V.G. and Gryzunov, V.V., Evaluation of the effectiveness of geographic information systems adaptation to destabilizing factors, J. Phys.: Conf. Ser., 2020, vol. 1703, p. 012016. https://doi.org/10.1088/1742-6596/1703/1/012016

    Article  Google Scholar 

  11. Zegzhda, D.P., Lavrova, D.S., and Pavlenko, E.Yu., Management of a dynamic infrastructure of complex systems under conditions of directed cyber attacks, J. Comput. Syst. Sci. Int., 2020, vol. 59, no. 3, pp. 358–370.  https://doi.org/10.1134/S1064230720020124

    Article  MATH  Google Scholar 

  12. Tatarnikova, T.M., Analytical-statistical model of mesh network survivability evaluation, Inf.-Upr. Sist., 2017, no. 1, pp. 17–22.  https://doi.org/10.15217/issnl684-8853.2017.1.17

  13. Tatarnikova, T.M. and Elizarov, M.A., Virtual channel simulation model, Nauch.-Tekh. Vestn. Inf. Tekhnol., Mekh. Opt., 2016, vol. 16, no. 6, pp. 1120–1127.  https://doi.org/10.17586/2226-1494-2016-16-6-1120-1127

    Article  Google Scholar 

  14. Sun, Y., Lin, F., and Xu, H., Multi-objective optimization of resource scheduling in fog computing using an improved NSGA-II, Wireless Pers. Commun., 2018, vol. 102, no. 2, pp. 1369–1385. https://doi.org/10.1007/s11277-017-5200-5

    Article  Google Scholar 

  15. Jia, B., Hu, H., Zeng, Y., Xu, T., and Yang, Y., Double-matching resource allocation strategy in fog computing networks based on cost efficiency, J. Commun. Networks, 2018, vol. 20, no. 3, pp. 237–246.  https://doi.org/10.1109/JCN.2018.000036

    Article  Google Scholar 

  16. Melnik, E.V., Klimenko, A.B., and Klimenko, V.V., Information and control system computational tasks distribution technique in the edge- and for-computing environments, Izv. Tul. Gos. Univ. Tekh. Nauki, 2019, no. 2, pp. 320–330.

Download references

Funding

This work was supported by the Ministry of Education and Science of the Russian Federation (information security grant), project no. 08/2020.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to V. V. Gryzunov.

Ethics declarations

The authors declare that they have no conflicts of interest.

Additional information

Translated by L. Mukhortova

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Gryzunov, V.V. Conceptual Model for Adaptive Control of a Geographic Information System under Conditions of Destabilization. Aut. Control Comp. Sci. 55, 1222–1227 (2021). https://doi.org/10.3103/S0146411621080381

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.3103/S0146411621080381

Keywords

Navigation