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Dynamic Voltage-Frequency and Workload Joint Scaling Power Management for Energy Harvesting Multi-Core WSN Node SoC

This paper proposes a scheduling and power management solution for energy harvesting heterogeneous multi-core WSN node SoC such that the system continues to operate perennially and uses the harvested energy efficiently. The solution consists of a heterogeneous multi-core system oriented task schedul...

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Detalles Bibliográficos
Autores principales: Li, Xiangyu, Xie, Nijie, Tian, Xinyue
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5336092/
https://www.ncbi.nlm.nih.gov/pubmed/28208730
http://dx.doi.org/10.3390/s17020310
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author Li, Xiangyu
Xie, Nijie
Tian, Xinyue
author_facet Li, Xiangyu
Xie, Nijie
Tian, Xinyue
author_sort Li, Xiangyu
collection PubMed
description This paper proposes a scheduling and power management solution for energy harvesting heterogeneous multi-core WSN node SoC such that the system continues to operate perennially and uses the harvested energy efficiently. The solution consists of a heterogeneous multi-core system oriented task scheduling algorithm and a low-complexity dynamic workload scaling and configuration optimization algorithm suitable for light-weight platforms. Moreover, considering the power consumption of most WSN applications have the characteristic of data dependent behavior, we introduce branches handling mechanism into the solution as well. The experimental result shows that the proposed algorithm can operate in real-time on a lightweight embedded processor (MSP430), and that it can make a system do more valuable works and make more than 99.9% use of the power budget.
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spelling pubmed-53360922017-03-16 Dynamic Voltage-Frequency and Workload Joint Scaling Power Management for Energy Harvesting Multi-Core WSN Node SoC Li, Xiangyu Xie, Nijie Tian, Xinyue Sensors (Basel) Article This paper proposes a scheduling and power management solution for energy harvesting heterogeneous multi-core WSN node SoC such that the system continues to operate perennially and uses the harvested energy efficiently. The solution consists of a heterogeneous multi-core system oriented task scheduling algorithm and a low-complexity dynamic workload scaling and configuration optimization algorithm suitable for light-weight platforms. Moreover, considering the power consumption of most WSN applications have the characteristic of data dependent behavior, we introduce branches handling mechanism into the solution as well. The experimental result shows that the proposed algorithm can operate in real-time on a lightweight embedded processor (MSP430), and that it can make a system do more valuable works and make more than 99.9% use of the power budget. MDPI 2017-02-08 /pmc/articles/PMC5336092/ /pubmed/28208730 http://dx.doi.org/10.3390/s17020310 Text en © 2017 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Li, Xiangyu
Xie, Nijie
Tian, Xinyue
Dynamic Voltage-Frequency and Workload Joint Scaling Power Management for Energy Harvesting Multi-Core WSN Node SoC
title Dynamic Voltage-Frequency and Workload Joint Scaling Power Management for Energy Harvesting Multi-Core WSN Node SoC
title_full Dynamic Voltage-Frequency and Workload Joint Scaling Power Management for Energy Harvesting Multi-Core WSN Node SoC
title_fullStr Dynamic Voltage-Frequency and Workload Joint Scaling Power Management for Energy Harvesting Multi-Core WSN Node SoC
title_full_unstemmed Dynamic Voltage-Frequency and Workload Joint Scaling Power Management for Energy Harvesting Multi-Core WSN Node SoC
title_short Dynamic Voltage-Frequency and Workload Joint Scaling Power Management for Energy Harvesting Multi-Core WSN Node SoC
title_sort dynamic voltage-frequency and workload joint scaling power management for energy harvesting multi-core wsn node soc
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5336092/
https://www.ncbi.nlm.nih.gov/pubmed/28208730
http://dx.doi.org/10.3390/s17020310
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AT tianxinyue dynamicvoltagefrequencyandworkloadjointscalingpowermanagementforenergyharvestingmulticorewsnnodesoc