Optimization of Datacenter Selection Policy in Cloud Computing using Differential Evolution Algorithm

Cloud computing has become one of the most influential inventions in modern-day computer science. It has become one of the integral parts of our day-to-day life. The success of our regular activities relies on the efficiency and effectiveness of the cloud services. The datacenter selection policy is one of the vital elements in cloud computing. The user requests are processed in the datacenter. Therefore, an optimal datacenter ensures user satisfaction with cloud services. In this research, we propose a differential evolution-based datacenter selection policy to choose the optimal datacenter for the userbase. Differential evolution mainly depends on the evolutionary process of mutation, which helps the algorithm explore the whole search space and find the optimal datacenter. We have used the Cloud Analyst simulator to experiment with the correctness and performance of our algorithm. The simulation results demonstrate that the proposed differential evolution algorithm performs better than the existing datacenter selection algorithm, such as the closest datacenter selection policy and optimized response time policy.