Service composition with knowledge of quality in the cloud environment using the cuckoo optimization and artificial bee colony algorithms

With the advent of cloud computing and the increasing of web service providers, a large number of non-functional services with the same or different properties such as time, availability, reliability and delay have been published on the web. When a service is not able to answer the applicator alone, the service composition to respond the user requests can be useful. The purpose is finding the best combination of services with awareness of quality, so that the high quality of combination and low response time to customer are achieved. Evaluation of all combinations of these services is very time consuming and is a part of NP-HARD Problem. In this paper, a new method for service composition using the cuckoo optimization algorithm (COA) and artificial bee colony (ABC) algorithm is proposed. With important aspects for a cloud computing based on qualitative parameters (QOS) in real environment, the simulation is performed in this paper. The simulation results of the proposed approach are showed the effective combination with high performance. Moreover, in this paper, the dynamic cloud environment and appropriate objective function are a major consideration.