A Bayesian Nash Equilibrium of QoS-Aware Web Service Composition

An important issue in QoS-aware Web service composition is how to select a set of Web services to perform the tasks within a requested service while meeting global QoS constraints. We consider the Web services are self-interested and will use dynamic pricing strategy. In general, the service cost is the minimum price acceptable to a Web service. We can obtain a composite Web service with the maximum utility by assigning the tasks to the Web services with the lowest costs. A Web service usually will not expose his cost, and thus, we face a decision making problem with incomplete information. Recent approaches use iterative combinatorial auction to address the problem. However, truthful bidding is not optimal strategy for Web services in these approaches. In this paper, we propose an incentive mechanism for choosing the optimal Web service for each task and show there exists a Bayesian Nash equilibrium of Web services, in which each Web service will bid truthfully. Finally, the experimental results show that our mechanism outperforms the existing combinatorial auction-based approaches.