Multiobjective Optimization in the Cloud Computing Environment for Storage Service Selection

Many cloud services are currently available to provide services for users in cloud environment. By the advent of the internet of things(IoT), the importance of cloud processing is increased. One of the services in cloud providers is storage service. Since the energy consumption and the fair distribution of load between the servers are significant for satisfying the Quality of service(QoS) constraint, lot of research has been done in this regard. To respond faster to users, we use the architecture of the edge computing. Furthermore, to prevent overload in one service, we decide to make decisions in one layer before the cloud service providers’ layer. In this article, we use the MOWCA algorithm which is running in Fog-layer. We evaluate our algorithm with other algorithms that have been mentioned earlier in this regard. The Pareto’s results have improvements in both energy consumption and Load Balancing between solutions while satisfying the spacing metric.