Analysis of Meta-Heuristics Performance in Energy Aware Scheduling of Real-Time Embedded Systems

被引:0
|
作者
Suyyagh, Ashraf [1 ]
Tong, Jason G. [1 ]
Zilic, Zeljko [1 ]
机构
[1] McGill Univ, Dept Elect & Comp Engn, Montreal, PQ H2X 2P1, Canada
关键词
GENETIC ALGORITHM;
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Energy efficient real-time systems has been a prime concern in the last few years. Techniques on all levels of system design from the physical up to operating system level are being developed to reduce energy consumption. Dynamic Voltage and Frequency Scaling (DVFS) and Dynamic Power Management (DPM) are among the most widely used methods. Most research efforts focused on reducing processor power. Recently, system-wide solutions have been investigated. In this work, we extend on the previous work by adapting two evolutionary algorithms for system-wide energy minimisation. We show that our meta-heuristics improve on previous work and are three times more likely to reach near-optimal energy savings.
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页数:6
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