A Composite Service Selection Method Supporting Service-Sharing across Multi-SLAs

In cloud computing environments, each service-oriented application is often instantiated with multiple workflow instances, and each of them provides a specific QoS level for a particular user category. In recent researches, most of works deploy service instances for each workflow independently, and the sharing of service instance is not considered across compositions related with different SLAs. This may cause several high-performance service instances are exclusively accessed by specific workflow instances, which can incur the following two issues: First, the remaining service instances cannot satisfy SLA for other users when high-performance ones are monopolized by some requests. Second, the utilization ratio of high-performance services will be decreased. To address these problems, a service composition model supporting the instances sharing in multiple SLA environments is provided in this paper. Since the QoS-aware service composition problem is known as NP-hard, which needs a significant amount of computation time to discover optimal solutions, a solving method based on multi-objective genetic algorithm, called MSCS, is proposed to solve it heuristically. The effectiveness of this approach is demonstrated via experiments.