Abstract. Specifics of communication infrastructure based on a content-controlled network are discussed. The purpose is to solve the problem of constructing an information and communication environment that provides data transfer from sources to consumers and allows for the possibility of software reconfiguration. An approach to virtualization of the data transmission medium is developed, based on encapsulation of related components, which makes it possible to consider the data transmission channel as a service or a virtual entity including a transmission medium, a set of hardware and software tools for transforming data flows between different physical environments, hardware and software for controlling transport streams, as well as hardware and software for encoding-decoding content. A distinctive feature of the approach is the use of active data technology (code fragments transmitted over the network and executed on network nodes), which enables the virtual data transmission medium to be considered as a distributed virtual machine, while the virtualization process is controlled by active data. To formalize the approach, multilayer graphs are used and modified to describe not only the network topology, but also the internal structure of nodes based on computing (software or hardware) components and interfaces. Using the proposed approach, a functional diagram of the implementation of a distributed information and communication environment based on a system of virtual machines is developed. Variants of interaction between nodes and distribution of executable code among network nodes in such an environment are considered and analyzed.

Keywords: active data, virtual machine, digital software-defined systems, cyber-physical systems, distributed network of virtual machines

References:

1. Volkova V.N., Leonova A.E., Loginova A.V., Cherny Yu.Yu. Journal of Applied Informatics, 2019, no. 1(14), pp. 68–81. (in Russ.)
2. Nguyen V.-C., Dinh N.-Th., Kim Y. Sensors (Basel, Switzerland), 2018, no. 18, pp. 4136, DOI:10.3390/s18124136.
3. Okhtilev M.Yu., Sokolov B.V., Shcherbakova E.E. Informatizatsiya i svyaz', 2020, no. 2, pp. 52–60. (in Russ.)
4. Levonevskiy D.K. Modelirovaniye, optimizatsiya i informatsionnyye tekhnologii, 2019, no. 4(7), pp. 16–17. (in Russ.)
5. https://habr.com/en/company/toshibarus/blog/438262/. (in Russ.)
6. Kuleshov S., Yusupov R. Informatics and Automation (SPIIRAS Proceedings), 2016, no. 46, pp. 5–13.
7. Alexandrov V.V., Kuleshov S.V., Zaytseva A.A. Smart Electromechanical Systems, Studies in Systems, Decision and Control, 2016, no. 49, pp. 61–69.
8. Alexandrov V.V., Kuleshov S.V., Tsvetkov O.V., Zaitseva А.А. Informatics and Automation (SPIIRAS Proceedings), 2008, no. 6, pp. 51–57 (in Russ.)
9. Kuleshov S.V., Aksenov A.Y., Zaytseva A.A. Advances in Intelligent Systems and Computing, 2017, vol. 575, рр. 326–330.
10. Kuleshov S.V., Zaytseva A.A., Aksenov A.Y. International Journal of Intelligent Unmanned Systems, 2018, no. 4(6), pp. 174–183, DOI 10.1108/IJIUS-04-2018-0010.
11. Kuleshov S.V., Zaytseva A.A., Ronzhin A.L. CPS&C 2019, Lecture Notes in Networks and Systems, Springer, 2020, no. 95, pp. 1–9, DOI: https://doi.org/10.1007/978-3-030-34983-7_25.
12. Kuleshov S.V., Zaytseva A.A., Shal'nev I.O. Information and Control Systems, 2019, no. 5, pp. 30–37, DOI:10.31799/1684-8853-2019-5-30-37.
13. Park Y., Yang H., Dinh Th. and Kim Y. International Journal of Distributed Sensor Networks, 2017, no. 13, https://doi.org/10.1177/1550147717717864.
14. Liu Y., Yu S.Z. Journal of Network and Computer Applications, 2016, no. 64, pp. 167–175, https://doi.org/10.1016/j.jnca.2016.02.007.
15. http://pt.journal.kh.ua/2010/2/2/102_ageyev_layer.pdf.