Q-Graphplan: QoS-Aware Automatic Service Composition With the Extended Planning Graph

Abstract

With the progress of web technologies, web services with abundant functionalities, such as video transmission, location, navigation, etc., are becoming more and more pervasive. Automatic web service composition aims to automatically combine selected elementary web services from a finite service set by matching the input and output parameters given an initial state and a goal state. Considering the end-to-end Quality-of-Service(QoS) of each web service, the service composition problem becomes an optimization problem to find the optimal solution. This paper maps this problem to an automatic planning problem and proposes Q-Graphplan based on the classical graphplan, an efficient planner for solving classical planning problems. First, we construct a planning graph based on the dependency relationships of the web services and extract essential heuristics according to the reachability analysis. Second, we convert this planning graph to a directed path generation graph. Finally, we extract the optimal solution from the path generation graph using a backward A* algorithm with the heuristics of the planning graph. Furthermore, our approach avoids redundancies when constructing the planning graph and improves the searching effectiveness in extracting solution. We conduct experiments on the WSC-2009 dataset to compare performance against present approaches, and the results show the efficiency and effectiveness of our proposed approach.

Keywords

• Service composition
• AI planning
• QoS-aware
• heuristic search