GRID RESOURCE PREDICTION APPROACH BASED ON NU-SUPPORT VECTOR REGRESSION

摘要：

One of the challenging problems in Grid environment is the choice of destination nodes where the tasks of the application are to be executed. Therefore, resource prediction is a crucial direction for job scheduling system and Grid users. In this paper, Nu-Support Vector Regression (v-SVR) is applied to solve resource prediction problem. The method of Parallel Multidimensional Step Search is also introduced to select parameters for v-SVR prediction model. Standard v-SVR method is extended to a systematic approach for Grid developer and user to finish preprocessing of data set and model optimization with high prediction accuracy. Experiments with resource data set were performed on computing nodes in Grid environment. Statistical analysis shows that our approach can automatically locate suitable parameters for building prediction model with high accuracy and remarkably reduce the computational time of model optimization.

关键词： Nu-support vector regression Parameter selection Grid computing Resource prediction Parallel Multidimensional Step Search

作者: XI-LONG CHE LIANG HU

作者单位: Department of Computer Science and Technology, Jilin University, No.2699 Qianjin Street, Changchun 130012, China

会议类型: 国际会议

会议名称: 2008 International Conference on Machine Learning and Cybernetics(2008机器学习与控制论国际会议)

会议地点: 昆明

会议语种:英文

页码: 778-783

在线出版日期: 2008-07-12（万方平台首次上网日期，不代表论文的发表时间）