Research On Cloud Computing Resource Algorithm In Smart Campus Information System

With the development of information technology,campus construction gradually get rid of the traditional management mode,from digital campus to smart campus has become the inevitable trend of campus development,various Internet application products continue to emerge in the campus environment,the cloud computing technology into smart campus new choice.At present,the amount of data storage is more and more complex,how to optimize the integration of resources,has become an urgent need to solve the problem of intelligent campus.Based on the research of cloud computing technology and the characteristics of cloud services,this paper focuses on the research and discussion of cloud computing technology data center resource algorithm.The main problems solved in this paper are as follows:Through the cloud computing technology as the basic structure of the framework,you can break the data island phenomenon.Considering the task independent subsystem of campus administrative system,teaching system,scientific research system,library system,the system and other original development,easy sharing and data exchange of information,subject to achieve data interoperability,each subsystem of the campus of the bulk transfer,as to realize the information fusion between the various systems sharing platform,achieve the smart campus information system integration.The cloud computing resource scheduling model,strategy and target of data center,a new method is proposed.According to the characteristics of multi-dimensional vector virtual machine virtual machine provides a resource allocation algorithm based on multi-objective evolutionary algorithm,is given according to the performance of vector comprehensive load capacity evaluation strategy,based on the historical load data trigger migration strategy,based on migration cost orientation strategy implementation,based on the best match of the migration of virtual target machine selection strategy four strategies.Through four strategies,while ensuring the application service performance,can effectively reduce the number of virtual machine migration,reduce the impact on the migration of the overall performance of cloud computing center,and to some extent reduce the number of virtual servers enabled,improve server resource utilization.Finally,a dynamic scheduling algorithm and an improved multi-objective evolutionary algorithm are proposed to simulate the experimental results and their analysis to verify the effectiveness and reliability of the proposed algorithm.