J. Low Power Electron. Appl. 2014, 4(2), 90-109; doi:10.3390/jlpea4020090
Article

A Practical Framework to Study Low-Power Scheduling Algorithms on Real-Time and Embedded Systems

1,* email, 2email and 2email
Received: 29 January 2014; in revised form: 18 March 2014 / Accepted: 10 April 2014 / Published: 7 May 2014
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract: With the advanced technology used to design VLSI (Very Large Scale Integration) circuits, low-power and energy-efficiency have played important roles for hardware and software implementation. Real-time scheduling is one of the fields that has attracted extensive attention to design low-power, embedded/real-time systems. The dynamic voltage scaling (DVS) and CPU shut-down are the two most popular techniques used to design the algorithms. In this paper, we firstly review the fundamental advances in the research of energy-efficient, real-time scheduling. Then, a unified framework with a real Intel PXA255 Xscale processor, namely real-energy, is designed, which can be used to measure the real performance of the algorithms. We conduct a case study to evaluate several classical algorithms by using the framework. The energy efficiency and the quantitative difference in their performance, as well as the practical issues found in the implementation of these algorithms are discussed. Our experiments show a gap between the theoretical and real results. Our framework not only gives researchers a tool to evaluate their system designs, but also helps them to bridge this gap in their future works.
Keywords: real-time/embedded systems; low-power; scheduling
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MDPI and ACS Style

Lin, J.; Cheng, A.M.K.; Song, W. A Practical Framework to Study Low-Power Scheduling Algorithms on Real-Time and Embedded Systems. J. Low Power Electron. Appl. 2014, 4, 90-109.

AMA Style

Lin J, Cheng AMK, Song W. A Practical Framework to Study Low-Power Scheduling Algorithms on Real-Time and Embedded Systems. Journal of Low Power Electronics and Applications. 2014; 4(2):90-109.

Chicago/Turabian Style

Lin, Jian; Cheng, Albert M.K.; Song, Wei. 2014. "A Practical Framework to Study Low-Power Scheduling Algorithms on Real-Time and Embedded Systems." J. Low Power Electron. Appl. 4, no. 2: 90-109.

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