Research on Dynamic Virtual Machine Scheduling Strategy Based on Improved Genetic Algorithm

In the actual application, when the virtual machine is created and the virtual machine is dynamically migrated, only the memory utilization of the host is considered, and other resource indicators, such as CPU utilization, are not considered, so the resource utilization may be unbalanced. This leads to unreasonable allocation of cloud computing resources in virtual machine scheduling. In order to solve the above problems, this paper proposes a dynamic virtual machine scheduling strategy based on improved genetic algorithm, which fully considers the CPU utilization and memory utilization of the host, and obtains the minimum dynamic migration overhead virtual machine scheduling scheme under the condition that the above resource utilization is relatively balanced. Finally, the algorithm was verified by CloudSim simulation experiment. Experimental data prove that the proposed algorithm has balanced resource utilization and effectively solves the load imbalance problem in virtual machine scheduling.