Adaptive power management based on reinforcement learning for embedded system

被引：0

作者：

Liu, Cheng-ting ^{[1
]}

Hsu, Roy Chaoming ^{[1
]}

机构：

[1] Natl Chiayi Univ, Dept Comp Sci & Informat Engn, Chiayi 60004, Taiwan

来源：

NEW FRONTIERS IN APPLIED ARTIFICIAL INTELLIGENCE | 2008年 / 5027卷

关键词：

adaptive power management; embedded system; reinforcement learning;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this study, an adaptive power management method based on reinforcement learning is proposed to improve the energy utilization and battery endurance for resource-limited embedded systems. A simulator which traces battery endurance and device operations is developed to examine the proposed method. Experimental results show that, in terms of battery efficiency and endurance, the performance of our proposed method is better than the traditional power management techniques, such as static power management method.

引用

页码：513 / 522

页数：10

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