A Novel Cloud Data Center Resource Scheduling Optimization Model based on KPCA and Markov Chain

Rapid development of the engineering science and technology has pushed forwarded the fast development of the cloud computing and the relate applications, under this basis, this paper proposes the novel cloud data center resource scheduling optimization model based on KPCA and Markov chain. How carries on the reasonable scheduling of resources, reduces the energy as far as possible the consumption, already became an important question. But, domestic and foreign mainly concentrates at present to the scheduling of the resources research in the reduction duty execution time improves in the grade of service, but to conserves energy the dispatch relatively the research few. For a private cloud, enterprise data center as a hardware platform, for the public cloud, enterprises at the center of the data as the backbone of the building resources, running on the cloud service is also more complicated and diverse, and more to the requirement of reliability, manageability, refinement. With this basis, this paper proposes the KPCA and Markov chain based model to deal with the challenges, the experiment verifies the robustness.