ORGANIZATION OF SCIENTIFIC COMPUTATIONS MANAGEMENT IN THE PACKAGE OF APPLIED MICROSERVICES
Abstract
In recent years, the integration of distributed and cloud computing technologies is observed in solving complex applied problems. The hybrid environment combines the reliability and availability of software running on local computers with the ability to scale computing to the cloud in peak load situations. The complexity of exhaustive problems with the properties of large-scale, openness, un-predictable dynamics, mobility of components determines the urgency of developing microservice-oriented software for solving them in a hybrid environment. The objective of the research is the fur-ther improvement of previously developed tools that automate the creation and use of an applied microservices package to organize the management of scientific computing in such an environment. A distributed computing model is represented by a set of autonomous computing microservices. Microservices' interaction is controlled by a self-organizing multi-agent system. Features of the architecture of agents and their functioning models are considered, they enable organizing parallel and pipeline-parallel multivariate calculations in a hybrid environment. We describe an example of usage of the applied microservices package based on the developed tools to solve the problems of qualitative analysis of binary dynamic systems. Solving these problems is based on the authors' Bool-ean constraint method. Based on this method, the feasibility verification of the required dynamical property is reduced to the feasibility check of constraints on the behavior of the trajectories of a dynamic system. For binary dynamical systems whose functioning is considered on a finite time interval, such restrictions are written in the language of Boolean equations or Boolean formulas with quantifiers. Our approach provides data parallelism and a significant increase in the dimension of the problems when solving them in a hybrid environment.
References
2. Netto M. A., Calheiros R. N., Rodrigues E.R., Cunha R.L., Buyya R. HPC Cloud for Scientific and Business Applications: Taxonomy, Vision, and Research Challenges, ACM CSUR, 2018, Vol. 51 (1), pp. 8:1-8:29.
3. Mell P., Grance T. The NIST Definition of Cloud Computing, 2011. Available at: https://nvlpubs.nist.gov/nistpubs/Legacy/SP/nistspecialpublication800-145.pdf (accessed 19 October 2019).
4. Bakshi K. Secure hybrid cloud computing: Approaches and use cases, IEEE Aerospace Con-ference, Big Sky, MT, 2014, pp. 1-8.
5. Merkel D., Santas F., Heberle A., Ploom T. Cloud Integration Patterns, 4th European Conference on Service-Oriented and Cloud Computing (ESOCC), Taormina, Italy, 2015, pp.199-213.
6. CSCC: Practical Guide to Cloud Computing. Available at: https://www.omg.org/cloud/deliverables/ CSCC-Practical-Guide-to-Hybrid-Cloud-Computing.pdf (accessed 19 October 2019).
7. Ochei L.C., Petrovski A., Bass J.M. A Novel Taxonomy of Deployment Patterns for Cloud-hosted Applications: A Case Study of Global Software Development (GSD) Tools and Pro-cesses, International Journal on Advances in Software, 2015, Vol. 8 (3 & 4), pp. 420-434.
8. Oparin G., Bogdanova V., Pashinin A. Qualitative analysis of autonomous synchronous binary dynamic systems, MESA, 2019, Vol. 10 (3), pp. 407-419.
9. Oparin G.A., Bogdanova V.G., Pashinin A.A., Gorsky S.A. Microservice-oriented Approach to Automation of Distributed Scientific Computations, Proceedings of 42st International Con-vention on Information and Communication Technology, Electronics and Microelectronics (MIPRO). Riejka: IEEE, 2019, pp. 253-258.
10. Ershov A.P. Nauchnoe osnovy dokazatel'nogo programmirovaniya [Scientific basis of evi-dence-based programming], Vestnik AN SSSR [Herald of the Russian Academy of Sciences], 1984, No. 10, pp. 9-19.
11. Newman S. Building Microservices. O’Reilly, 2015
12. Bychkov I.V., Oparin G.A., Bogdanova V.G., Pashinin A.A., Gorsky S.A. Automation Devel-opment Framework of Scalable Scientific Web Applications Based on Subject Domain Knowledge, In: Malyshkin V. (eds) Parallel Computing Technologies. PaCT 2017. Lecture Notes in Computer Science. Springer, Cham, 2017, Vol. 10421, pp. 278-288.
13. Bychkov I.V., Oparin G.A., Bogdanova V.G., Pashinin A.A. Servis-oriyentirovannaya tekhnologiya sozdaniya i primeneniya detsentralizovannykh multiagentnykh reshateley vychislitelnykh zadach [Service-oriented technology for development and application of de-centralized multiagent solvers for applied problems], Vestnik kompyuternykh i informatsionnykh tekhnologiy [Herald of computer and information technologies], 2018, No. 12, pp. 36-44.
14. Wang Y. Cloud-dew architecture, International Journal of Cloud Computing, 2015, Vol. 4 (3), pp. 199-210.
15. Bychkov I., Oparin G., Bogdanova V., Pashinin A. Intellectual technology for computation control in the package of applied microservices, Proceedings of the 1st International Work-shop on Information, Computation, and Control Systems for Distributed Environments 2019. CEUR WS Proceedings, 2019, Vol. 2430, pp. 15-28.
16. Bochmann D. Binare dinamische systeme. Christian Posthof, Berlin, 1981.
17. TSKP Irkutskiy superkomp'yuternyy tsentr SO RAN [Irkutsk Supercomputer Centre of SB RAS]. Available at: http://hpc.icc.ru/ (accessed 18 October 2019).
18. Available at: https://firstvds.ru/ (accessed 18 October 2019).
19. Dubrova E. Self-Organization for Fault-Tolerance. In: Hummel K.A., Sterbenz J.P.G. (eds) Self-Organizing Systems. IWSOS 2008. Lecture Notes in Computer Science. Springer, Berlin, Heidelberg, 2008, Vol. 5343, pp.145-156.
20. Dubrova E., Teslenko M. A SAT-Based Algorithm for Finding Short Cycles in Shift Register Based Stream Ciphers, IACR Cryptology ePrint Archive, 2016: 1068.
