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DOI: 10.14569/IJACSA.2016.071205
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Scheduling of Distributed Algorithms for Low Power Embedded Systems

Author 1: Stanislaw Deniziak
Author 2: Albert Dzitkowski

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 7 Issue 12, 2016.

  • Abstract and Keywords
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Abstract: Recently, the advent of embedded multicore processors has created interesting technologies for power management. Systems consisting of low-power and high-efficient cores create new possibilities for the optimization of power consumption. However, new design methods, dedicated to these technologies should be developed. In this paper we present a method of static task scheduling for low-power real-time embedded systems. We assume that the system is specified as a distributed algorithm, then it is implemented using multi-core embedded processor with low-power processing capabilities. We propose a new scheduling method to create the optimal or suboptimal schedule. The goal of optimization is to minimize the power consumption while all time constraints will be satisfied or the quality of service will be as high as possible. We present experimental results, obtained for sample systems, showing advantages of our method.

Keywords: Embedded system; distributed algorithm; task scheduling; big.LITTLE; low power system

Stanislaw Deniziak and Albert Dzitkowski, “Scheduling of Distributed Algorithms for Low Power Embedded Systems” International Journal of Advanced Computer Science and Applications(IJACSA), 7(12), 2016. http://dx.doi.org/10.14569/IJACSA.2016.071205

@article{Deniziak2016,
title = {Scheduling of Distributed Algorithms for Low Power Embedded Systems},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2016.071205},
url = {http://dx.doi.org/10.14569/IJACSA.2016.071205},
year = {2016},
publisher = {The Science and Information Organization},
volume = {7},
number = {12},
author = {Stanislaw Deniziak and Albert Dzitkowski}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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