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An Optimal and Complete Algorithm for Automatic Web Service Composition

An Optimal and Complete Algorithm for Automatic Web Service Composition

Pablo Rodriguez-Mier (University of Santiago de Compostela, Spain), Manuel Mucientes (University of Santiago de Compostela, Spain), Juan C. Vidal (University of Santiago de Compostela, Spain), and Manuel Lama (University of Santiago de Compostela, Spain)
Copyright: © 2012 |Volume: 9 |Issue: 2 |Pages: 20
ISSN: 1545-7362|EISSN: 1546-5004|EISBN13: 9781466614741|DOI: 10.4018/jwsr.2012040101
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MLA

Rodriguez-Mier, Pablo, et al. "An Optimal and Complete Algorithm for Automatic Web Service Composition." IJWSR vol.9, no.2 2012: pp.1-20. https://doi.org/10.4018/jwsr.2012040101

APA

Rodriguez-Mier, P., Mucientes, M., Vidal, J. C., & Lama, M. (2012). An Optimal and Complete Algorithm for Automatic Web Service Composition. International Journal of Web Services Research (IJWSR), 9(2), 1-20. https://doi.org/10.4018/jwsr.2012040101

Chicago

Rodriguez-Mier, Pablo, et al. "An Optimal and Complete Algorithm for Automatic Web Service Composition," International Journal of Web Services Research (IJWSR) 9, no.2: 1-20. https://doi.org/10.4018/jwsr.2012040101

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Abstract

The ability of web services to build and integrate loosely-coupled systems has attracted a great deal of attention from researchers in the field of the automatic web service composition. The combination of different web services to build complex systems can be carried out using different control structures to coordinate the execution flow and, therefore, finding the optimal combination of web services represents a non-trivial search effort. Furthermore, the time restrictions together with the growing number of available services complicate further the composition problem. In this paper the authors present an optimal and complete algorithm which finds all valid compositions from the point of view of the semantic input-output message structure matching. Given a request, a service dependency graph which represents a suboptimal solution is dynamically generated. Then, the solution is improved using a backward heuristic search based on the A* algorithm which finds all the possible solutions with different number of services and runpath. Moreover, in order to improve the scalability of our approach, a set of dynamic optimization techniques have been included. The proposal has been validated using eight different repositories from the Web Service Challenge 2008, obtaining all optimal solutions with minimal overhead.

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