非平稳自相似业务下自适应动态功耗管理  

Adaptive Dynamic Power Management for Non-Stationary Self-Similar Requests

作　　者：吴琦[1] 熊光泽[1] 

机构地区：[1]电子科技大学计算机科学与工程学院,四川成都610054

出　　处：《软件学报》2005年第8期1499-1505,共7页Journal of Software

基　　金：No.2003AA1Z2210国家高技术研究发展计划(863)~~

摘　　要：动态功耗管理(dynamicpowermanagement,简称DPM)是一种优化计算机设备能量消耗的设计技术,优化效果依赖于采用的功耗管理策略和控制算法.研究表明,传统排队论的指数分布假设不适用于DPM策略研究,DPM最优策略是超时策略,超时策略可以获得很好的节能效果的理论原因是计算机系统业务请求具有自相似性.提出了当空闲时间长度服从Pareto分布时,基于截尾均值法小样本情况下Pareto分布形状参数的稳健有效估计算法和基于窗口大小自适应技术非平稳业务请求下的DPM控制算法.实验结果表明,该算法具有很好的稳定性,在不考虑其他条件约束时,竞争率可降到1.24,在延迟率小于0.10的条件下,竞争率可降到1.47,而且算法计算负荷小.Dynamic power management （DPM） is a design methodology aiming at reducing power consumption of electronic systems. The effectiveness of a power management scheme depends critically on the power management policy and control algorithm. In this work, it is found that the exponential distribution supposition taken by traditional queuing theory is not suitable to DPM, and the timeout policy is enough for DMP. The reason that the simple timeout policy could reduce much energy consumption of computer devices is the self-similarity nature of computer service requests. This paper proposes an adaptive control algorithm for DPM of embedded operating system when the idle time length fits Pareto distribution. It adopts the Trimmed Mean Estimator to realize the robust efficient estimation of the tail index parameter of Pareto distribution for small sample size, and is implemented using window-size-based adaptive control method. Simulation results show that the algorithm presented in this paper is robust. The competitive ratio is reduced to 1.24 and even 1.47 when the delay is smaller than 0.10. Overhead of the adaptive control algorithm is low.

关 键 词：自相似 PARETO分布 自适应 动态功耗管理 参数估计 

分 类 号：TP316[自动化与计算机技术—计算机软件与理论]