Presenting an Optimal Algorithm for Resource Scheduling and Code Partition in Mobile Cloud Computing

Through virtualization technology, current cloud data centers are becoming more flexible and secure, and are allocated on demand. A key technology playing an important role in cloud data centers is the resource scheduling program. In this paper, a near-optimal strategy is proposed to solve the problems in this field, by using an evolutionary particle swarm algorithm to reduce the range of multiple targets to a proper level. The placement method based on the particle swarm optimization algorithm can act as real-time placement, due to the increase in computational capability of processors over the past five years. This placement is a searching method in which competencies are dynamically altered based on the variance of fitness values ​​in each generation. This migration and placement approach also minimizes the completion time for virtual machines. In order to assess the proposed method, the results were analyzed and compared through various qualitative criteria, from different aspects and based on changes in different functioning parameters. The performance of the proposed method was compared with other approaches in this field and reflects the high quality of the proposed method.