[1] Huang Gang, Wang Ruchuan, Xie Yongjuan, Shi Xiaojuan, et al. Load prediction of grid computing resourcesbased on ARSVR method [J]. Journal of Southeast University (English Edition), 2009, 25 (4): 451-455. [doi:10.3969/j.issn.1003-7985.2009.04.007]
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Load prediction of grid computing resourcesbased on ARSVR method(
)
基于ARSVR方法的网格计算资源负载预测
)Journal of Southeast University (English Edition)[ISSN:1003-7985/CN:32-1325/N]
- Volumn:
- 25
- Issue:
- 2009 4
- Page:
- 451-455
- Research Field:
- Computer Science and Engineering
- Publishing date:
- 2009-12-30
Info
- Title:
- Load prediction of grid computing resourcesbased on ARSVR method
- 基于ARSVR方法的网格计算资源负载预测
- Author(s):
- Huang Gang; Wang Ruchuan; Xie Yongjuan; Shi Xiaojuan
- College of Computer, Nanjing University of Posts and Telecommunications, Nanjing 210003, China
- Keywords:
- grid; autoregressive support vector regression algorithm; computing resource; load prediction
- 网格; 自回归支持向量回归机算法; 计算资源; 负载预测
- PACS:
- TP393
- DOI:
- 10.3969/j.issn.1003-7985.2009.04.007
- Abstract:
- Based on the monitoring and discovery service 4(MDS4)model, a monitoring model for a data grid which supports reliable storage and intrusion tolerance is designed. The load characteristics and indicators of computing resources in the monitoring model are analyzed. Then, a time-series autoregre-ssive prediction model is devised. And an autoregressive support vector regression(ARSVR)monitoring method is put forward to predict the node load of the data grid.Finally, a model for histo-rical observations sequences is set up using the autoregressive(AR)model and the model order is determined.The support vector regression(SVR)model is trained using historical data and the regression function is obtained. Simulation results show that the ARSVR method can effectively predict the node load.
- 在MDS4监控模型的基础上, 设计了基于可靠存储与容侵数据网格的监控模型, 分析了监控模型中计算资源的负载特性、指标. 然后, 设计了基于SVR的时间序列自回归预测模型, 提出了用于数据网格负载预测的监控ARSVR方法. 最后, 利用AR模型对历史观测序列进行建模, 确定模型的阶次. 根据历史数据对SVR进行训练, 得到回归函数. 仿真实验结果表明, ARSVR方法能对节点的负载进行有效预测.
References:
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Memo
- Memo:
-
Biography: Huang Gang(1961—), male, associate professor, huanggang@njupt.edu.cn.
Foundation item: The National High Technology Research and Development Program of China(863 Program)(No.2007AA01Z404).
Citation: Huang Gang, Wang Ruchuan, Xie Yongjuan, et al. Load prediction of grid computing resources based on ARSVR method[J]. Journal of Southeast University(English Edition), 2009, 25(4): 451-455.