Title: Optimality and scalability of semantic web service composition with hierarchical parameter relationship

Authors: John Jung-Woon Yoo; Jaffer Sadiq Mughal; Fariborz Tayyari

Addresses: Department of Industrial and Manufacturing Engineering and Technology, Caterpillar College of Engineering and Technology, Bradley University, Peoria, IL, USA ' Department of Industrial and Manufacturing Engineering and Technology, Caterpillar College of Engineering and Technology, Bradley University, Peoria, IL, USA ' Department of Industrial and Manufacturing Engineering and Technology, Caterpillar College of Engineering and Technology, Bradley University, Peoria, IL, USA

Abstract: Semantic web service composition considers semantics for finding better solutions than syntactic web service composition. This paper focuses on hierarchical relationships among parameters of web services. A comprehensive mathematical model for semantic web service composition, into which hierarchical parameter relationships are incorporated, is presented as a general mathematical formulation. Experimental results demonstrate that the mathematical model for semantic composition finds hidden and better solutions that syntactic composition cannot find. The optimality of the solutions is empirically verified through extensive experiments. Furthermore, the scalability of the model is tested by comprehensive experiments to explore the impacts of eight key factors on web service composition. The mathematical model and the provided datasets are expected to serve as benchmarking tools for performance evaluation of heuristic algorithms for semantic web service composition. Finally, a web application is presented to visualise the semantic web service composition process, which is developed using the Django framework.

Keywords: AI planning; web service composition; semantics; parameter hierarchy; mathematical modelling.

DOI: 10.1504/IJWGS.2025.147119

International Journal of Web and Grid Services, 2025 Vol.21 No.2, pp.138 - 162

Received: 13 Feb 2024
Accepted: 04 Jul 2024
Published online: 10 Jul 2025 *

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