作　　者： ; ; ; ; ;

机构地区： 惠州学院计算机科学系

出　　处： 《浙江大学学报（理学版）》 2014年第3期353-357,共5页

摘　　要： 为实现海量大数据的高效访问与处理,在资源与服务发现的基础上,探讨了一种云格环境下使用网络距离预测的方法来完成计算资源服务节点的选择机制.并从提高系统性能的角度,针对用户偏好,提出了一种可计算资源与服务的高效调配模型,来实现密集型数据的高性能计算;最后实验验证了本调配模型具有的可行性与针对性. In order to implement massive big data access and process with high efficiency, based on the discovery of resource and service, a mechanism on selection of service nodes for the computational resources is explored by using the method of networking distance prediction under GLOUD. Then considering the indicator of system performance including response time, resources utilization and access cost and others, a resources and services provisioning model is proposed to implement data intensive computing with high efficiency from the view of user＇s preference. Finally experiment shows that the provisioning model is available and pertinently.

关 键 词： 云格环境 网络距离预测 资源与服务 调配模型

领　　域： [自动化与计算机技术] [自动化与计算机技术]