A KPN based Model for Describing and Verifying the Interaction of Web Services

Li Bao, Le Hao

Abstract


Correct interaction between Web services is essential for successful Web service composition. This paper proposes a Web
Service Interaction Model (IWSN) that aims to ensure correct interaction between Web services, improve the scalability of Web service
composition, solve behavioral compatibility issues in the process of Web service interaction, and promote the application of service
composition technology in related fields. The Kahn Process Network (KPN) supports parallel computing based on data streams and
channels, and the proposed Web Service Interaction Model in this article is based on the KPN. The formal semantics of the IWSN model are
based on process algebra Pi calculus, and the model's properties are discussed. Finally, an application case is used to demonstrate how the
IWSN model can be applied to Web service composition and interaction.

Keywords


Web Service, Service Composition, Service Interaction, Process algebra

Full Text:

PDF

Included Database


References


[1] Meng Wei. Research on the Development Path and Countermeasures of an Open Service Economy [J] Economic Forum, 2017, 4: 124-125

[2] Varghese, Blesson, Buyya, et al. Next generation cloud computing: New trends and research directions[J]. Future Generations Computer Systems Fgcs,

2018, 79(3): 849-861.

[3] Canal C., Villari M.. Advances in Service-Oriented and Cloud Computing[M]. Springer International Publishing, 2015.

[4] PengWei Wang, ZhiJun Ding, ChangJun Jiang. Constrain-Aware Approach to Web Service Composition[J]. IEEE Transactions on Systems Man &

Cybernetics Systems, 2014, 44(6): 770-784.

[5] A. L. Lemos, F. Daniel, B. Benatallah. Web service composition: a survey of techniques and tools[J]. ACM Computing Surveys (CSUR), 2015, 48(3): 1-41.

[6] Li C, Guan J, Liu T, et al. An autonomy-oriented method for service composition and optimal selection in cloud manufacturing[J]. International Journal of

Advanced Manufacturing Technology, 2018, 96(3): 1-22.

[7] Arul U, Prakash S. Toward automatic web service composition based on multilevel workflow orchestration and semantic web service discovery[J].

International Journal of Business Information Systems, 2020, 34(1): 128-156.

[8] P. Rodriguez-Mier, M. Mucientes, M. Lama. Hybrid Optimization Algorithm for Large-Scale QoS-Aware Service Composition[J]. IEEE Transactions on

Service Computing, 2017, 10(4): 547-559.

[9] Sun Zuhan, Li Ying, Lo Chi Ling, etc. . Design and implementation of a visual REST service composition framework[J]. Small microcomputer systems,

2017,38(1) : 10-14.

[10] Song Y, Gong Y. Web service composition on IoT reliability test based on cross entropy[J]. Computational Intelligence, 2020, 36(4): 1650-1662.

[11] H. Wang, X. Chen, Q. Wu, et al. Integrating reinforcement learning with multi-agent techniques for adaptive service composition[J]. ACM Transactions

on Autonomous and Adaptive Systems (TAAS), 2017, 12(2): 1-42.

[12] F. Seghir, A. Khababa. A hybrid approach using generic and fruit fl y optimization algorithms for QoS-aware cloud service composition[J]. Journal of Intelligent Manufacturing, 2017: 1-20.

[13] G. Kahn. The semantics of a simple language for parallel programming[J]. Information processing, 1974, 74: 471-475.

[14] Milner R, Communication and Mobile Systems: The Pi-Calculus[M], Cambridge University Press, 1999.

[15] E.M.Clarke, E.A.Emerson, and A.P.Sistla. Automatic verification of finite-state concurrent systems using temporal logic specifications[J]. ACM

Transaction on ProgrammingLanguages and Systems,1986, 8(2): 244-263.




DOI: https://doi.org/10.18686/esta.v10i2.350

Refbacks

  • There are currently no refbacks.


Copyright (c) 2023 Li Bao,Le Hao