Aliakbar Tajari Siahmarzkooh - Assistant Professor Department of Computer Sciences, Faculty of Sciences Golestan University Gorgan, Iran,

Load balancing tasks on the cloud environment is an important aspect of data center distribution. According to calculations of the Internet; Cloud computing struggles with overload requests. Load balancing should be done in such a way that all virtual machines have a balanced load to achieve optimal use of their capabilities. In this paper, a new method of load balancing among virtual machines is presented using a combination of PSO and a ML algorithm. The goal is to combine increasing machine performance with load balancing between virtual machines and maintaining a balance between task priorities by optimizing waiting times for tasks. A comparison of the simulation results of the real platform shows that our proposed algorithm performed better than other approaches.

load balancy; cloud computing; machine learning; particle swarm optimization.