Web service composition enables the provision/reusing of existing services in different business processes to satisfy different business requirements without investing in new infrastructure. QoS-aware web service composition seeks to help users find the optimal solution with maximization of users' satisfaction. A number of approaches based on Communicating Sequential Processes (CSP) have been proposed to model and verify properties of web service composition. However, little work has been done in verifying inputs, outputs and QoS criteria of web service composition. In this paper, we present a framework to model and verify QoS-aware web service composition by Timed CSP. It helps verify whether the service composition can accept inputs, generate outputs, and meet QoS requirements as specified. To do the verification, transformation rules that map QoS-aware web service composition to Timed CSP are defined. In order to explain the framework and transformation rules, we design a case study, where the model of QoSaware web service composition is transformed to the model of process composition in Timed CSP and the program in machine-readable CSP (CSPM). Furthermore, experiments are performed by using the Failure Divergence Refinement (FDR) tool to verify inputs, outputs, and QoS of the service composition.
With the development of cloud computing, more and more applications are posted online to provide services for users. Since user needs can be complex, an individual service will not able to meet the requirement. Web Service Composition composes multiple web services together to fulfil the complicated user requirement. While searching an optimal composition with both functional and non-functional requirements still is a challenging problem that needs to be addressed. QoS-aware web service composition is an NP-hard problem. To solve this problem, we design a system which combines GraphPlan with Fuzzy Control algorithm. Fuzzy Control is employed to generate overall QoS according to user preferences. In the forward phase of Graphplan, less competitive services are pruned according to the overall QoS. In the backward phase, services are selected according to functional goals and their overall QoS. Furthermore, case study and are performed, and the experimental results show that our approach improves the quality of service composition significantly compared with ordinary and Skyline approach.
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