Journal of Systems and Software
Verifying mediated service interactions considering expected behaviours
Journal of Network and Computer Applications
WI-IAT '11 Proceedings of the 2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Volume 01
Multi-criteria service selection with optimal stopping in dynamic service-oriented systems
ICDCIT'10 Proceedings of the 6th international conference on Distributed Computing and Internet Technology
Exploring information diffusion in network of semantically annotated web service interfaces
Proceedings of the 2nd International Conference on Web Intelligence, Mining and Semantics
QoS-aware automatic service composition: a graph view
Journal of Computer Science and Technology - Special issue on Community Analysis and Information Recommendation
A dynamic qos-aware semantic web service composition algorithm
ICSOC'12 Proceedings of the 10th international conference on Service-Oriented Computing
ICCCI'12 Proceedings of the 4th international conference on Computational Collective Intelligence: technologies and applications - Volume Part II
Composite web QoS with workflow conditional pathways using bounded sets
Service Oriented Computing and Applications
Accurate sub-swarms particle swarm optimization algorithm for service composition
Journal of Systems and Software
Web Intelligence and Agent Systems
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The main research focus of Web services is to achieve the interoperability between distributed and heterogeneous applications. Therefore, flexible composition of Web services to fulfill the given challenging requirements is one of the most important objectives in this research field. However, until now, service composition has been largely an error-prone and tedious process. Furthermore, as the number of available web services increases, finding the right Web services to satisfy the given goal becomes intractable. In this paper, toward these issues, we propose an AI planning-based framework that enables the automatic composition of Web services, and explore the following issues. First, we formulate the Web-service composition problem in terms of AI planning and network optimization problems to investigate its complexity in detail. Second, we analyze publicly available Web service sets using network analysis techniques. Third, we develop a novel Web-service benchmark tool called WSBen. Fourth, we develop a novel AI planning-based heuristic Web-service composition algorithm named WSPR. Finally, we conduct extensive experiments to verify WSPR against state-of-the-art AI planners. It is our hope that both WSPR and WSBen will provide useful insights for researchers to develop Web-service discovery and composition algorithms, and software.