Forming Ontologies and Dynamically Configurable Infrastructures at the Stage of Transition to Digital Economy Based on Logistics

  • Sergey Barykin
  • Stanislav Gazul
  • Vladimir Kiyaev
  • Olga KalininaEmail author
  • Vladimir Yadykin
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1116)


Digitalization of all economic sectors results in continuously increasing load on corporate data processing centers. There is decrease of economic efficiency for using classic methods of developing information infrastructures of organizations. The purpose of this article is to provide the non-classical description of the current situation in the IT development conceptual field and the conceptual description of the intellectual computing platform of modern organization in the digital globalization context.


Virtualization Computing containers Logistics Multi-agent systems Data center Cloud computing 


  1. 1.
    Feoktistov, A., Sidorov, I., Sergeev, V., Kostromin, R., Bogdanova, V.: Virtualization of heterogeneous HPC-clusters based on OpenStack platform. Bull. S. Ural State Univ. Ser. Comput. Math. Soft. Eng. 6(2), 37–48 (2017)Google Scholar
  2. 2.
    Kalinina, O., Balchik, E., Barykin, S.: Innovative management neural network modelling based on logistic theory. In: 2018 MATEC Web of Conferences (2018)CrossRefGoogle Scholar
  3. 3.
    Myougnjin, K., Hanku, L., Hyogun, Y., Jee-In, K., HyungSeok, K.: IMAV: an intelligent multi-agent model based on cloud computing for resource virtualization. In: 2011 International Conference on Information and Electronics Engineering IPCSIT, vol. 6 (2011)Google Scholar
  4. 4.
    Pourmajidi, W., Miranskyy, A.: Logchain: blockchain-assisted log storage. In: IEEE International Conference on Cloud Computing, CLOUD, pp. 978–982. IEEE Computer Society, San Francisco (2018Google Scholar
  5. 5.
    Shekhtman, L.M., Waisbard, E.: Securing log files through blockchain technology. In: SYSTOR 2018 - Proceedings of the 11th ACM International Systems and Storage Conference, p. 131. Association for Computing Machinery, Haifa (2018)Google Scholar
  6. 6.
    Trofimov, V., Kiyaev, V., Gazul, S.: Use of virtualization and container technology for information infrastructure generation. In: Proceedings of 2017 20th IEEE International Conference on Soft Computing and Measurements, SCM 2017, Saint Petersburg, Russian Federation, pp. 788–791 (2017)Google Scholar
  7. 7.
    Taherizadeh, S., Stankovski, V., Grobelnik, M.: A capillary computing architecture for dynamic internet of things: orchestration of microservices from edge devices to fog and cloud providers. Sensors 18(9) (2018). Article no. 2938CrossRefGoogle Scholar
  8. 8.
    Taherizadeh, S., Jones, A.C., Taylor, I., Zhao, Z., Stankovski, V.: Monitoring self-adaptive applications within edge computing frameworks: a state-of-the-art review. J. Syst. Softw. 136, 19–38 (2018)CrossRefGoogle Scholar
  9. 9.
    Yusupov, R., Musaev, A.: Efficiency of information systems and technologies: features of estimation. SPIIRAS Proc. 2(51), 5–34 (2017)CrossRefGoogle Scholar
  10. 10.
    Vasileva, O., Kiyaev, V.: Generation of efficient cargo operation schedule at seaport with the use of multiagent technologies and genetic algorithms. In: Abraham, A., Snasel, V., Kovalev, S., Sukhanov, A., Tarassov, V. (eds.) Proceedings of the 3rd International Scientific Conference on Intelligent Information Technologies for Industry, IITI 2018, Advances in intelligent systems and computing, vol. 874, pp. 401–409. Springer, Heidelberg (2018)Google Scholar
  11. 11.
    Vilken, V., Kalinina, O., Barykin, S., Zotova, E.: Logistic methodology of development of the regional digital economy. In: IOP Conference Series: Materials Science and Engineering (2019)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Peter the Great St. Petersburg Polytechnic UniversitySt. PetersburgRussian Federation
  2. 2.Saint Petersburg State University of EconomicsSt. PetersburgRussian Federation

Personalised recommendations