Apply Rough Set Theory into the Web Services Composition

Abstract

Web services are being adopted, more and more, as a viable means of accessing Web-based applications. At present, there is a trend towards deploying business processes as composite Web services, known as Web services compositions. Web services compositions are synthesized by researchers from elementary Web services, offering the opportunity for service providers and application developers to create value-added services, through Web services composition. However, a problem exists in the current distribution process of Web services compositions: the general analysis and selection of services can be overly complex and un-systemic. Genetic algorithms (GA) has been widely used to solve optimization problems for large scale and complex systems. However, when insufficient knowledge is incorporated, GA is less efficient in terms of searching for an optimal solution. This paper develops a generic genetic algorithm incorporating knowledge extracted from the rough set theory. The advantages of the proposed solution approach include improving the performance of the GA by reducing the domain range of initial population, rule constraining crossover process and rule constrained mutation process, using the rough set theory for composite Web services. Also by proposing the hybrid approach, the GA and rough set theory can operate effectively thus to produce an optimal solution (the best combination of Web services).