非平稳多任务下的动态功耗管理随机策略  

Dynamic power management stochastic policy for non-stationary multi-task

作　　者：马喜强[1,2] 刘维亚[1] 郑喜凤[1] 程鹏[1,2] 

机构地区：[1]中国科学院长春光学精密机械与物理研究所,长春130033 [2]中国科学院大学,北京100039

出　　处：《吉林大学学报（工学版）》2014年第3期776-781,共6页Journal of Jilin University:Engineering and Technology Edition

基　　金：国家科技支撑计划项目(2009BAE73B01)

摘　　要：基于系统信息建立了任务的设备利用率统计查找表,并根据实际的间隔时间更新分布。然后,建立了半Markov随机模型,定义了代价函数和目标优化函数,并给出了平均准则下基于线性规划的求取最优策略的方法。试验结果表明:在考虑性能约束的条件下,该算法具有很好的稳定性;延迟率小于0.10;竞争率可以达到0.57。更稳定、有效地降低了功耗,有利于在嵌入式系统中应用。A dynamic power management stochastic policy for non-stationary multi-task is proposed. First, device-requester utilization lookup table was constructed based on system message, and distribution was updated according to the actual time interval. Then, a Semi-Markov stochastic model was built, and the cost function and objective function were defined. The discount criteria optimization method based on linear programming strategy was given. The moment of decision and conversion state was pointed out. Experimental results show that, while considering the conditions of the performance constraints, the algorithm has good stability; delay rate is less than 0. 10; competitive rate can reach 0.57. The algorithm reduces power consumption more efficiently than other policies, and is beneficial to the application in embedded systems.

关 键 词：计算机应用 动态功耗管理 MARKOV决策过程 策略优化 嵌入式系统 

分 类 号：TP301[自动化与计算机技术—计算机系统结构]