Deep Learning Inspired Hybrid Meta-Heuristic Approach For Intelligent Service Composition In Dynamic Cloud Environment

Current generation computing scenarios evidenced proliferation of cloud services with the rapid growth in the cloud service consumers. Demand for the utilization of cloud services is constantly increasing with complex service requests from the cloud service consumers that lead to the service composition. Functionally similar cloud services are being offered by different cloud service providers that made the selection of optimal cloud service as an multi-objective optimization problem. In this research study a deep learning inspired metaheuristic approach is devised that with stand the continuous demands from different consumers in the context of selecting optimal composition pattern in dynamic cloud environment. The experimental studies indicate that the integration of deep learning mechanism with meta-heuristic optimization algorithm depicts better performance results than the existing meta heuristic approaches of cloud service composition.