Scientific Services Consolidation Methods


The article discusses methods of consolidating scientific services of a digital platform for integrating a set of scientific services for various fields of science for conducting interdisciplinary research. Solutions for creating consolidated services can be widely used for multilevel, multiscale modeling in the field of materials science, which provides complex modeling at several levels of the hierarchy. Currently, this problem is being solved by creating multicomponent hierarchical software systems on corporate computing systems. With the advent of high-performance cloud computing platforms, it will be possible to order services for solving particular modeling problems as a scientific service. In this case, the tasks of complex hierarchical modeling will be solved by a consolidated service—a service providing sequential-parallel execution of complex modeling components in the form of specialized scientific services. The description of the processes for the provision of scientific services is based on the research methodology and is a research plan (the work process mapping), which describes a set of operations related to time and includes a list of necessary resources for their implementation. In modern conditions of the development of a microservice approach to the creation of computing systems and the evolution of the Service Oriented Architecture and of the Enterprise Service Bus integration, special attention is paid to the problems of efficient integration of platform services. The paper proposes to supplement the existing description of a scientific service with the possibility of ordering a third-party service based on agile integration. This approach will allow at the present stage of development of service architectures to overcome the shortcomings of centralized systems such as Enterprise Service Bus and take advantage of the elasticity of cloud computing and a microservice approach to creating information and computing systems.

This is a preview of subscription content, access via your institution.


  1. 1

    Abgaryan, K.K., Informatsionnaya tekhnologiya postroeniya mnogomasshtabnykh modelei v zadachakh vychislitel’nogo materialovedeniya (Information Technology is the Construction of Multi-Scale Models in Problems of Computational Materials Science), Moscow: Radiotekhnika, 2018, pp. 9–15.

  2. 2

    Abgaryan, K.K., Gavrilov, E.S., and Marasanov, A.M., Multiscale modeling for composite materials computer simulation support, Int. J. Open Inform. Technol., 2017, vol. 5, no. 2, pp. 24–28.

    Google Scholar 

  3. 3

    Clark, K., Curcio, T., and Glowacki, N., Agile integration architecture, IBM, 2018. Accessed March 11, 2020.

  4. 4

    Mell, P. and Grance, T., NIST SP 800-145, The NIST Definition of Cloud Computing. Recommendations of the National Institute of Standards and Technology, Gaithersburg: NIST, 2011. Legacy/SP/nistspecialpublication800-145.pdf. Accessed March 11, 2020.

  5. 5

    Zatsarinny, A.A., Gorshenin, A.K., Volovich, K.I., Kolin, K.K., Kondrashev, V.A., and Stepanov, P.V., Management of scientific services as the basis of the national digital platform ‘Science and Education,’ Strateg. Priorit., 2017, no. 2 (14), pp. 103–114.

  6. 6

    Lewis, J. and Fowler M., Microservices. Accessed March 11, 2020.

  7. 7

    Newman, S., Building Microservices: Designing Fine-Grained Systems, USA: O’Reilly Media, 2015.

    Google Scholar 

  8. 8

    Kreger, H., Brunssen, V., Sawyer, R., Arsanjani, A., and High, R., The IBM advantage for SOA reference architecture standards, in IBM Developer Works, 2012. ws-soa-ref-arch/ws-soa-ref-arch-pdf.pdf. Accessed March 11, 2020.

  9. 9

    Keen, M. et al., Patterns: Implementing an SOA Using an Enterprise Service Bus, IBM Redbooks, 2004. Accessed March 11, 2020.

  10. 10

    Clark, K., The fate of the ESB, IBM Developer, 2018. Accessed March 11, 2020.

  11. 11

    Clark, K., Comparing web APIs with service-oriented architecture and enterprise application integration, IBM Developer, 2015. technologies/web-development/articles/comparing-web-apis-with-service-oriented-architecture-and-enterprise-application-integration/. Accessed March 11, 2020.

  12. 12

    Volovich, K.I., Organization of calculations in a hybrid high-performance computing cluster for parallel execution of heterogeneous tasks, Sist. Sredstva Inform., 2018, vol. 28, no. 4, pp. 98–108.

    Google Scholar 

  13. 13

    Regulations of CKP ‘Informatika.’ Accessed March 11, 2020.

Download references


This research is partially supported by the Russian Foundation for Basic Research (projects 18-29-03091, 19-29-03051) using the resources of the CKP ‘Informatics.’

Author information



Corresponding authors

Correspondence to A. A. Zatsarinny or V. A. Kondrashev or A. A. Sorokin or S. A. Denisov.

Additional information

This article was prepared based on a report presented at the 1st International Conference on “Mathematical Modeling in Materials Science of Electronic Components” (Moscow, 2019).

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Zatsarinny, A.A., Kondrashev, V.A., Sorokin, A.A. et al. Scientific Services Consolidation Methods. Russ Microelectron 49, 612–616 (2020).

Download citation


  • consolidated service
  • multiscale modeling
  • multilevel modeling
  • digital platform
  • сloud сomputing
  • scientific service
  • service integration