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

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

1,* , 2
1 Department of Management Information Systems, University of Houston—Clear Lake, Houston,TX 77058, USA 2 Department of Computer Science, University of Houston, Houston, TX 77204, USA
* Author to whom correspondence should be addressed.
Received: 29 January 2014 / Revised: 18 March 2014 / Accepted: 10 April 2014 / Published: 7 May 2014
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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 real-time/embedded systems; low-power; scheduling
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.

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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.

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J. Low Power Electron. Appl. EISSN 2079-9268 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert