Estimation and Analysis of Embedded Operating System Energy Consumption (1.Institute of Software,School of Electronics Engineering and Computer Science,Peking University, Key laboratory of High Confidence Software Technologies ,Ministry of Education,Beijing 100871,China; 2.College of Computer Science and Technology,Beijing Technology and Business University,Beijing 100037,China)
ZHAO Xia, GUO Yao, LEI Zhi-Yong, et al. Estimation and Analysis of Embedded Operating System Energy Consumption (1.Institute of Software,School of Electronics Engineering and Computer Science,Peking University, Key laboratory of High Confidence Software Technologies ,Ministry of Education,Beijing 100871,China; 2.College of Computer Science and Technology,Beijing Technology and Business University,Beijing 100037,China)[J]. Acta Electronica Sinica, 2008, 36(2): 209-215.
ZHAO Xia, GUO Yao, LEI Zhi-Yong, et al. Estimation and Analysis of Embedded Operating System Energy Consumption (1.Institute of Software,School of Electronics Engineering and Computer Science,Peking University, Key laboratory of High Confidence Software Technologies ,Ministry of Education,Beijing 100871,China; 2.College of Computer Science and Technology,Beijing Technology and Business University,Beijing 100037,China)[J]. Acta Electronica Sinica, 2008, 36(2): 209-215.DOI:
With the progress of low-power research on embedded systems
the estimation and analysis of the energy consumption of operating system becomes a hot topic.This paper presents a quantitative approach to estimate and analyze the energy consumption of embedded operating system (EOS).In this approach
EOS and applications are executed on two cooperated simulators.Instruction execution energy is estimated using a cycle-accurate micro-architecture power model.We propose an OS energy consumption estimation model based on software functionality and structure.The approach can calculate the energy consumption for functions
routines
services and kernel execution paths in an EOS
and can identify the key modules and factors impacting the system energy consumption.Our experiments show that the proposed approach improves the accuracy and efficiency of energy estimation of EOS significantly.The estimation results can be used to quantitatively analyze and optimize the energy consumption of EOS and applications.