The Virtual Machine Placement Strategy Research In Cloud Environment

As the core infrastructure of cloud computing services,cloud data centers use virtualization technology to consolidate the resources of physical server cluster systems and efficiently manage resources and applications in the cloud environment.The business volume of cloud computing services continues to expand,and the procurement costs of hardware and software caused by the expansion of cloud platform continue to increase.Unreasonable resource allocation methods cause a lot of waste of resources,and the problem of low utilization rate of system resources becomes increasingly prominent.Therefore,the virtual environment under cloud environment Machine placement strategy has become a research hotspot in the current field.This article aims to solve the problem of the energy consumption and system performance balance of the cloud computing center.Currently,for the virtual machine placement strategy in the cloud environment,domestic and foreign scholars have conducted in-depth research,but there are still many key issues that need to be resolved.This article summarizes these issues,and then combines the cloud computing technology and virtualization technology,gives the placement strategy of virtual machines in the cloud environment.The main research content of this article is as follows.(1)Finishing and summarizing the mainstream virtual machine placement strategies and the issues that need to be solved in the commercial operation of the cloud platform under the cloud environment,and then establishing an optimization model based on the three goals of energy power,load balancing ratio and SLA compliance rate,and then converting them into mathematical models.Solve.(2)In order to solve the conflict between the above three different optimization target models,a multi-objective optimization-based virtual machine placement strategy is proposed to balance the conflict between different optimization objectives,and an optimal solution that can balance three goals can be obtained globally..(3)Modeling the problem of virtual machine placement under cloud environment,and then converting it into a packing problem,and then using the multi-objective optimization genetic algorithm proposed in this paper to solve.Finally,the process of multi-objective optimization genetic algorithm is introduced in detail.Using the advantages of population and self evolution of genetic algorithm,it can reduce the number of open physical servers and effectively balance three different conditions while ensuring the SLA fulfillment rate and load balancing rate.The goal of optimization.(4)programming to achieve the proposed multi-objective optimization genetic algorithm,using the CloudSim platform for simulation experiments.The algorithm flow is designed and experimental results are obtained.The traditional best-fit heuristic algorithm,singleobjective simple genetic algorithm and multi-objective optimization genetic algorithm are implemented respectively.Comparing experimental results The multi-objective optimization genetic algorithm proposed in this paper can effectively reduce the number of physical servers under the condition of satisfying higher SLA fulfillment rate and load balancing ratio.