Cloud service ranking as a multi objective optimization problem

Cloud computing is a kind of computing model on subscription basis. In cloud computing environment, there are a lot of cloud providers that present variety kind of services with different quality of services. Users have various kinds of applications that should be carried out on suitable cloud services. Consequently the users might encounter problems in choosing the best service. Hence selection of a method to compare services and to choose best service has been regarded as a challenge. In this paper we presented NSGA_SR approach that utilizes both objective and subjective assessments and models ranking problem as a multi objective optimization and then solves it with use of non-dominated sorting genetic algorithm. Numerical experiments, confirmed that the proposed approach outperforms available approaches in terms of flexibility and scalability with increasing number of users and services. Also it converges to optimization of goals and has good stability during the different generations. Also it includes no limitation regarding any additive new quality attribute, service or supplementary function.