Discovery and composition of web services using artificial intelligence planning and web service modeling ontology

Abstract

In today’s Web environment, Web services are the preferred standards-based way to realize Service Oriented Architecture (SOA) computing. A problem that has become one of the recent critical issues is automated discovery and composition of Semantic Web services. A number of approaches have been presented to solve the problem. However, most of these approaches only consider discovery or composition of Web services but not both. In this study, an effective approach called AIMO, based on Artificial Intelligence (AI) planning, Web Service Modeling Ontology (WSMO), and Semantic Web has been proposed to tackle the problem. The main purpose of this study is to investigate and develop a novel approach for automated Web service discovery and composition. In this case, a comparative evaluation of state-of-the-art approaches for Web service composition approaches has been done and the strengths and weaknesses of those approaches have been discussed. Moreover a translator for interaction between WSMO and AI-planning based on Description Logics has been proposed. In addition, some parts of AIMO architecture have been tested on a practical case study, and the results based on the experimental validation demonstrate that AIMO provides an effective and applicable solution. AIMO continues to support loose coupling paradigm of SOA by separating the discovery from the composition of Web services.