Cost-driven web service selection using genetic algorithm

Web services composition has been one of the hottest research topics. But with the ever increasing number of functional similar web services being made available on the Internet, there is a need to be able to distinguish them using a set of well-defined Quality of Service (QoS) criteria. The cost is the primary concern of many business processes. In this paper, we propose a new solution using Genetic Algorithm (GA) in cost-driven web service selection. GA is utilized to optimize business process composed of many service agents (SAg). Each SAg corresponds to a collection of available web services provided by multiple service providers to perform a specific function, Service selection is an optimization process with taking into account the relationships among the services. Better performance has been gotten using GA in the paper than using local service selection strategy. The global optimal solution might also be achieved with proper GA parameters.