Wireless sensor nodes are becoming more and more common in various settings and require a long battery life for better maintainability. Since most sensor nodes are powered by batteries, energy efficiency is a critical problem. In an experiment, we observed that when peak power consumption is high, battery voltage drops quickly, and the sensor stops working even though some useful charge remains in the battery. We propose three off-line algorithms that extend battery life by scheduling sensors' execution time that is able to reduce peak power consumption as much as possible under a deadline constraint. We also developed a simulator to evaluate the effectiveness of these algorithms. The simulation results showed that one of the three algorithms dramatically can extend battery life approximately three time as long as in simultaneous sensor activation.
Qian ZHAO
University of Hyogo
Yukikazu NAKAMOTO
University of Hyogo
Shimpei YAMADA
University of Hyogo
Koutaro YAMAMURA
NEC System Technologies Limited
Makoto IWATA
NEC System Technologies Limited
Masayoshi KAI
NEC System Technologies Limited
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Qian ZHAO, Yukikazu NAKAMOTO, Shimpei YAMADA, Koutaro YAMAMURA, Makoto IWATA, Masayoshi KAI, "Sensor Scheduling Algorithms for Extending Battery Life in a Sensor Node" in IEICE TRANSACTIONS on Fundamentals,
vol. E96-A, no. 6, pp. 1236-1244, June 2013, doi: 10.1587/transfun.E96.A.1236.
Abstract: Wireless sensor nodes are becoming more and more common in various settings and require a long battery life for better maintainability. Since most sensor nodes are powered by batteries, energy efficiency is a critical problem. In an experiment, we observed that when peak power consumption is high, battery voltage drops quickly, and the sensor stops working even though some useful charge remains in the battery. We propose three off-line algorithms that extend battery life by scheduling sensors' execution time that is able to reduce peak power consumption as much as possible under a deadline constraint. We also developed a simulator to evaluate the effectiveness of these algorithms. The simulation results showed that one of the three algorithms dramatically can extend battery life approximately three time as long as in simultaneous sensor activation.
URL: https://globals.ieice.org/en_transactions/fundamentals/10.1587/transfun.E96.A.1236/_p
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@ARTICLE{e96-a_6_1236,
author={Qian ZHAO, Yukikazu NAKAMOTO, Shimpei YAMADA, Koutaro YAMAMURA, Makoto IWATA, Masayoshi KAI, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Sensor Scheduling Algorithms for Extending Battery Life in a Sensor Node},
year={2013},
volume={E96-A},
number={6},
pages={1236-1244},
abstract={Wireless sensor nodes are becoming more and more common in various settings and require a long battery life for better maintainability. Since most sensor nodes are powered by batteries, energy efficiency is a critical problem. In an experiment, we observed that when peak power consumption is high, battery voltage drops quickly, and the sensor stops working even though some useful charge remains in the battery. We propose three off-line algorithms that extend battery life by scheduling sensors' execution time that is able to reduce peak power consumption as much as possible under a deadline constraint. We also developed a simulator to evaluate the effectiveness of these algorithms. The simulation results showed that one of the three algorithms dramatically can extend battery life approximately three time as long as in simultaneous sensor activation.},
keywords={},
doi={10.1587/transfun.E96.A.1236},
ISSN={1745-1337},
month={June},}
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TY - JOUR
TI - Sensor Scheduling Algorithms for Extending Battery Life in a Sensor Node
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 1236
EP - 1244
AU - Qian ZHAO
AU - Yukikazu NAKAMOTO
AU - Shimpei YAMADA
AU - Koutaro YAMAMURA
AU - Makoto IWATA
AU - Masayoshi KAI
PY - 2013
DO - 10.1587/transfun.E96.A.1236
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E96-A
IS - 6
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - June 2013
AB - Wireless sensor nodes are becoming more and more common in various settings and require a long battery life for better maintainability. Since most sensor nodes are powered by batteries, energy efficiency is a critical problem. In an experiment, we observed that when peak power consumption is high, battery voltage drops quickly, and the sensor stops working even though some useful charge remains in the battery. We propose three off-line algorithms that extend battery life by scheduling sensors' execution time that is able to reduce peak power consumption as much as possible under a deadline constraint. We also developed a simulator to evaluate the effectiveness of these algorithms. The simulation results showed that one of the three algorithms dramatically can extend battery life approximately three time as long as in simultaneous sensor activation.
ER -