Task scheduling algorithm for virtual machines on cloud computing platforms

Abstract

Virtualization technology has been widely used to virtualize one server into multiple servers,which not only creates an operating environment for virtual machine-based cloud computing platforms but also has the ability to improve efficiency. its. Currently, most task scheduling algorithms used in cloud computing environments converge slowly or easily fall into local optimal states. This article introduces the greedy particle swarm optimization algorithm (G&PSO) to solve the task scheduling problem. The greedy algorithm is used to solve the initial element value of the swarm algorithm originating from a cloud-based virtual machine. Therefore, the performance and resources of the virtual machine used are improved compared to the traditional particle swarm optimization algorithm (PSO).