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.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Masdari, M., Nozad Bonab, M., Ozdemir, S.: QoS-driven metaheuristic service composition schemes: a comprehensive overview. Artif. Intell. Rev. 54, 3749–3816 (2021)
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
Valderas, P., Torres, V., Pelechano, V.: Towards the composition of services by end-users. Bus. Inf. Syst. Eng. 62(4), 305–321 (2020)
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
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)
Dara, N., Emadi, S.: Enriching web services tags to improve data-driven web services composition. J. Web Eng. 20(2), 327–358 (2021)
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)
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)
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)
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
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
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
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)