Skip to main content

A Graph-Based Service Composition Method for Science and Technology Resources

  • Conference paper
  • First Online:
Human Centered Computing (HCC 2021)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13795))

Included in the following conference series:

  • 330 Accesses

Abstract

Science and technology resources can be regarded as web services on the Internet, in order to realize the reuse of science and technology resources, the industry provides services for Internet users in multiple web service methods. In order to reuse of the web services, multiple web services need to be combined according to certain rules and business logic to solve the problem of limited functions of a single web service. The web service composition algorithm focuses on finding a service composition scheme with the best service quality. A single service composition scheme cannot cope with the dynamic changes of the network environment in real time, such as service failures. This paper proposes a graph-based service composition method, which uses the service dependency graph to establish the relationship between services, and combines the functional and non-functional attributes of the service. In the service selection stage, a formula for calculating the matching degree between the service and the target parameters is proposed to evaluate the current matching degree between the service and the target parameters, and the service with the best matching degree is selected.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 64.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 84.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Masdari, M., Nozad Bonab, M., Ozdemir, S.: QoS-driven metaheuristic service composition schemes: a comprehensive overview. Artif. Intell. Rev. 54, 3749–3816 (2021)

    Article  Google Scholar 

  2. Medema, M., Kaldeli, E., Lazovik, A.: Automated service composition using AI planning and beyond. In: Aiello, M., Bouguettaya, A., Tamburri, D.A., van den Heuvel, W.-J. (eds.) Next-Gen Digital Services. A Retrospective and Roadmap for Service Computing of the Future. LNCS, vol. 12521, pp. 16–32. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-73203-5_2

    Chapter  Google Scholar 

  3. Valderas, P., Torres, V., Pelechano, V.: Towards the composition of services by end-users. Bus. Inf. Syst. Eng. 62(4), 305–321 (2020)

    Article  Google Scholar 

  4. Lou, Q., Zhang, S.-Z., Song, W.W.: Combination of evaluation methods for assessing the quality of service for express delivery industry. In: Wang, J., et al. (eds.) WISE 2015. LNCS, vol. 9419, pp. 414–425. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-26187-4_39

    Chapter  Google Scholar 

  5. Viriyasitavat, W., Xu, L.D., Bi, Z., Sapsomboon, A.: Blockchain-based business process management (BPM) framework for service composition in Industry 4.0. J. Intell. Manuf. 31(7), 1737–1748 (2020)

    Google Scholar 

  6. Dara, N., Emadi, S.: Enriching web services tags to improve data-driven web services composition. J. Web Eng. 20(2), 327–358 (2021)

    Google Scholar 

  7. Xu, L., Sun, Q., Xu, B., Zhang, W.: Statically detect data races for WS-BPEL web services by constraint solver. In: ICWS 2016, pp. 476–483 (2016)

    Google Scholar 

  8. Taherkordi, A., Eliassen, F., Mcdonald, M., Horn, G.: Context-driven and real-time provisioning of data-centric IoT services in the cloud. ACM Trans. Internet Techn. 19(1), 7:1–7:24 (2019)

    Google Scholar 

  9. Michael, M., Llorca, J., Tulino, A.M.: Approximation algorithms for the optimal distribution of real-time stream-processing services. In: ICC 2019, pp. 1–7 (2019)

    Google Scholar 

  10. Blum, A.L., Furst, M.L.: Fast planning through planning graph analysis. Artif. Intell. 90(1–2), 281–300 (1997). https://doi.org/10.1016/S0004-3702(96)00047-1

    Article  MATH  Google Scholar 

Download references

Acknowledgement

The authors would like to express their thanks to the editors and experts who participated in the review of the paper for their valuable suggestions and comments. This research was supported by National Key Research and Development Project—R&D and application demonstration of comprehensive technology service platform for Beibu Gulf city group (2018YFB1404404), and Beijing Practical Training Project.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Changyou Zhang .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Tian, Z., Zhang, C., Xiao, J., Liang, S. (2022). A Graph-Based Service Composition Method for Science and Technology Resources. In: Zu, Q., Tang, Y., Mladenovic, V., Naseer, A., Wan, J. (eds) Human Centered Computing. HCC 2021. Lecture Notes in Computer Science, vol 13795. Springer, Cham. https://doi.org/10.1007/978-3-031-23741-6_23

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-23741-6_23

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-23740-9

  • Online ISBN: 978-3-031-23741-6

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics