Enhanced QoS-Based Service Composition Approach in Multi-Cloud Environment

The service composition problem in Cloud computing is formulated as a multiple criteria decision-making problem. Due to the extensive search space, Cloud service composition is addressed as an NP-hard problem. In addition, it is a long term based and economically driven. Composting accurate services have great attention to interest and importance for the Cloud consumer in the multi-Cloud environment. Therefore, an enhanced QoS-based Service Composition Approach in the multi-Cloud environment has been proposed to accurately compose the best Cloud providers to contract with them for composing the needed services to minimize the Cloud consumer cost function. In this paper, a modified Particle Swarm Optimization (PSO) has been employed to compose the best services based on the uncertainty of QoS attributes. The proposed approach has been implemented using a real QoS dataset. According to the comparative results, it is found that the proposed approach has achieved a high degree of optimality with low time complexity compared to the existing models.