QoS-driven optimal multi-cloud service composition using discrete and fuzzy integrated cuckoo search algorithm

Abstract

Recent generations of service computing evidence that quality of Service (QoS) driven optimal composition of multi-cloud services (QoS-CSC) is considered as a vital problem in the context of manufacturing complex cloud services based on the client requirements. Due to the proliferation of the seamless cloud services, optimal service composition of the multi-cloud services is considered as an NP-Hard problem. The QoS-CSC problems are solved by using continuous optimization algorithms to make them discrete a suitable encoding scheme is adopted with continuous optimization. In this paper, we propose a fuzzy integrated numerical encoding scheme in which the solution is represented as a fuzzy matrix and the composition of cloud services is obtained using that fuzzy matrix and further the global QoS attributes are computed. Discrete and Fuzzy integrated Cuckoo Search algorithm (DFCS) is developed by using our proposed fuzzy solution encoding schema. Further, during the process of performance evaluation, an empirical comparison various existing metaheuristic algorithms and proposed DFCS algorithm is illustrated using a set of real-world cloud services to identify exceptional service composition that optimizes local along with the global QoS attributes.