摘要
基于随机控制的策略优化算法能有效地解决动态电源管理(DPM)中电源状态切换的能耗问题,从而获得更优的策略.文中通过为系统建立基于马尔可夫决策过程的随机模型,在DPM框架中实现了DPM随机模型算法,并对算法进行了实验.结果表明,在不同的性能损耗条件下,可以得到不同的、满足性能要求的优化策略,也就是说,算法在性能和能量损耗间取得了平衡,这也证明了文中介绍的算法实现过程的可行性.
The policy-optimizing algorithms based on stochastic model can effectively reduce the power consumption of power state transitions for dynamic power management（DPM） and work out a better strategy.In this paper,a stochastic model based on Markov decision processes was established for the DPM system,and the corresponding algorithm was implemented in a material DPM architecture.Then,experiments for the algorithm were carried out.The results indicate that,with the proposed algorithm,different optimized policies satisfying performance requirements can be worked out in different power consumptions,that is,the algorithm strikes a balance between the performance and energy consumption.All this means that the algorithm implementation is feasible.
出处
《华南理工大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2007年第9期60-64,共5页
Journal of South China University of Technology(Natural Science Edition)
基金
国家"863"计划重大软件专项(2004AA1Z2400)
粤港关键领域重点突破项目(2005A10207005
信产厅2004-0005)
关键词
随机模型
马尔可夫链
动态电源管理
算法
stochastic model
Markov chain
dynamic power management
algorithm
