Service Adaptation with Probabilistic Partial Models

Abstract

Web service composition makes use of existing Web services to build complex business processes. Non-functional requirements are crucial for the Web service composition. In order to satisfy non-functional requirements when composing a Web service, one needs to rely on the estimated quality of the component services. However, estimation is seldom accurate especially in the dynamic environment. Hence, we propose a framework, ADFlow, to monitor and adapt the workflow of the Web service composition when necessary to maximize its ability to satisfy the non-functional requirements automatically. To reduce the monitoring overhead, ADFlow relies on asynchronous monitoring. ADFlow has been implemented and the evaluation has shown the effectiveness and efficiency of our approach. Given a composite service, ADFlow achieves 25 %–32 % of average improvement in the conformance of non-functional requirements, and only incurs 1 %–3 % of overhead with respect to the execution time. This work is supported by research project T2MOE1303.