Service-oriented Application Composition with Evolutionary Heuristics and Multiple Criteria

Abstract

The need to create and deploy business application systems rapidly has sparked interest in using web services to compose them. When creating mission-critical business applications through web service compositions, in addition to ensuring that functional requirements are met, designers need to consider the end-to-end reliability, security, performance, and overall cost of the application. As the number of available coarse-grain business services grows, the problem of selecting appropriate services quickly becomes combinatorially explosive for realistic-sized business applications. This article develops a business-process-driven approach for composing service-oriented applications. We use a combination of weights to explore the entire QoS criteria landscape through the use of a multi-criteria genetic algorithm (GA) to identify a Pareto-optimal multidimensional frontier that permits managers to trade off conflicting objectives when selecting a set of services. We illustrate the effectiveness of the approach by applying it to a real-world drop-ship business application and compare its performance to another GA-based approach for service composition.