非平稳服务请求下的功耗管理

马喜强; 宋喜佳; 刘维亚; 郑喜凤

doi:10.3788/OPE.20142207.1929

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非平稳服务请求下的功耗管理

信息科学 | 更新时间：2020-08-13

- 非平稳服务请求下的功耗管理
- Power-aware management for non-stationary service requests
- 光学精密工程 2014年22卷第7期页码：1929-1937
- 作者机构：
  
  1. 中国科学院大学北京,中国,100049
  2. 中国科学院长春光学精密机械与物理研究所,吉林长春,130033
- 作者简介：
- 基金信息：
  
  国家科技支撑计划资助项目（No.2009BAE73B01）()
- DOI：10.3788/OPE.20142207.1929
  中图分类号： TP273;TP301
- 收稿日期：2013-07-26，
  
  修回日期：2013-09-24，
  
  纸质出版日期：2014-07-25
- 稿件说明：
移动端阅览
马喜强, 宋喜佳, 刘维亚等. 非平稳服务请求下的功耗管理[J]. 光学精密工程, 2014,22(7): 1929-1937

MA Xi-qiang, Song Xi-jia, LIU Wei-ya etc. Power-aware management for non-stationary service requests[J]. Editorial Office of Optics and Precision Engineering, 2014,22(7): 1929-1937
马喜强, 宋喜佳, 刘维亚等. 非平稳服务请求下的功耗管理[J]. 光学精密工程, 2014,22(7): 1929-1937 DOI： 10.3788/OPE.20142207.1929.

MA Xi-qiang, Song Xi-jia, LIU Wei-ya etc. Power-aware management for non-stationary service requests[J]. Editorial Office of Optics and Precision Engineering, 2014,22(7): 1929-1937 DOI： 10.3788/OPE.20142207.1929.

摘要

针对嵌入式系统的多任务环境，提出了混合模型功耗管理算法，用于对服从一般分布的系统进行建模。首先，介绍了现有的动态功耗管理策略算法，阐述了算法需要改进的原因。然后，使用重标极差法（Rescaled Range Analysis，R/S）对非平稳服务请求下的时间序列进行长距离相关性分析；根据不同的分析结果选择相应的最大概率策略，即基于电池剩余电量的超时策略、模糊非标准PID策略和半Markov随机策略。最后，给出了策略参数的确定方法并通过实验的方法对本文提出的策略进行分析。实验结果表明，本文策略弥补了常规动态电源管理策略的不足，具有更广泛的适应性；在性能损失10%的条件下，系统平均功耗减少了37%，命中率大于60%，更稳定、有效地降低了功耗，有利于在嵌入式系统中应用。

Abstract

For multitasking environment of an embedded system

an improved method called hybrid model for power management algorithm was proposed for modeling of system with general distribution.First

the dynamic power management strategy algorithm was introduced

and the reason why it needed to be improved was expounded.Then

the Rescaled Range Analysis(R/S)method was used to analyze the long distance correlation of non-stationary time service requests and the corresponding strategy was selected depending on the different results.These strategies are remaining battery power timeout strategy

fuzzy not quite PID strategy and semi-Markov random strategy.Finally

the method for determining the strategy parameters was given and the strategy proposed in this paper was analyzed experimentally.The experimental results show that this strategy makes up for the deficiency of conventional dynamic power management strategy and has more extensive adaptability.Under the condition of 10% performance loss

the average system power consumption is reduced by 37%

and the hit rate is more than 60%.The algorithm reduces power consumption more efficiently than other methods

and is applicable in embedded systems.

关键词

Keywords

references

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