摘要
针对现有单一预测策略不适用于所有异构任务的问题,提出一种基于本地任务与远程任务运行时间的组合预测方案(CPS)和预测精度保证(PAA)的概念。使用Grid Sim工具集来实现CPS,将PAA作为定量评价由某一特定预测策略提供的预测运行时间精度的标准。仿真实验表明:与本地任务预测策略如Last和滑动窗口中值(SM)相比,CPS的平均相对残差下降了1.58%、1.62%;与远程任务预测策略如平均运行时间(RM)和加权移动平均值(ES)相比,CPS的平均相对残差下降了1.02%、2.9%。因此,PAA能从综合策略所提供的结果中选择接近最优值的预测,CPS增强了计算环境中本地任务和远程任务运行时间的PAA。
A Combined Prediction Scheme （CPS） and a concept of Prediction Accuracy Assurance （PAA） were put forward for the runtime of local and remote tasks, on the issue of inapplicability of the singleness policy to all the heterogeneous tasks. The toolkit of GridSim was used to implement the CPS, and PAA was a quantitative evaluation standard of the prediction runtime provided by a specific strategy. The simulation experiments showed that, compared with the local task prediction strategy such as Last and Sliding Median （SM）, the average relative residual error of CPS respectively reduced by 1.58% and 1.62% ; and compared with the remote task prediction strategy such as Running Mean （RM） and Exponential Smoothing （ES）, the average relative residual error of CPS respectively reduced by 1.02% and 2.9%. The results indicate that PAA can select the near-optimal value from the results of comprehensive prediction strategy, and CPS enhances the PAA of the runtime of local and remote tasks in the computing environments.
出处
《计算机应用》
CSCD
北大核心
2015年第8期2153-2157,2163,共6页
journal of Computer Applications
基金
国家自然科学基金资助项目(61370095
61370098
61070057
90715029)
湖南省教育厅科学研究项目(13C074)
衡阳市科技发展计划项目(2011KJ22)
湖南省教育科学"十二五"规划课题(XJK014CGD006)
关键词
计算集群
组合预测方案
预测精度保证
任务
运行时间
computing cluster
Combined Prediction Scheme （CPS）
Prediction Accuracy Assurance （PAA）
task
runtime
