Resource Scheduling Algorithm Based on Evolutionary Computation in Dynamic Cloud Environment

Abstract

The growing types of resources and changing user requirements in the cloud environment bring great challenges to the resource scheduling problem. In order to solve the problem of resource scheduling in dynamic cloud environment, this paper constructs a virtual dynamic cloud environment resource scheduling model, which realizes resource scheduling by means of virtual machine migration. In this model, the energy consumption of the cloud environment and the quality of service of the cloud environment after virtual machine migration are taken as two optimization objectives. At the same time, we propose a new dynamic multi-objective optimization algorithm (called DCRS-EA) to solve the resource scheduling problem in dynamic cloud environment. DCRS-EA not only detects whether the environment changes, but also estimates the types of changes, in which different types of change are solved by different response strategies. Finally, the experiments show the superior performance of DCRS-EA when comparing to other dynamic strategies on the built optimization model.