IEICE TRANSACTIONS on Communications
Multi-Battery Scheduling for Battery-Powered DVS Systems
Summary :
More and more mobile devices adopt multi-battery and dynamic voltage scaling policy (DVS) to reduce the energy consumption and extend the battery runtime. However, since the nonlinear characteristics of the multi-battery are not considered, the practical efficiency is not good enough. In order to reduce the energy consumption and extend the battery runtime, this paper proposes an approach based on the battery characteristics to implement the co-optimization of the multi-battery scheduling and dynamic voltage scaling on multi-battery powered systems. In this work, considering the nonlinear discharging characteristics of the existing batteries, we use the Markov process to depict the multi-battery discharging behavior, and build a multi-objective optimal model to denote the energy consumption and battery states, then propose a binary tree based algorithm to solve this model. By means of this method, we get an optimal and applicable scheme about multi-battery scheduling and dynamic voltage scaling. Experimental results show that this approach achieves an average improvement in battery runtime of 17.5% over the current methods in physical implementation.
- Publication
- IEICE TRANSACTIONS on Communications Vol.E95-B No.7 pp.2278-2285
- Publication Date
- 2012/07/01
- Publicized
- Online ISSN
- 1745-1345
- DOI
- 10.1587/transcom.E95.B.2278
- Type of Manuscript
- PAPER
- Category
- Energy in Electronics Communications
Authors
Keyword
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Peng OUYANG, Shouyi YIN, Leibo LIU, Shaojun WEI, "Multi-Battery Scheduling for Battery-Powered DVS Systems" in IEICE TRANSACTIONS on Communications,
vol. E95-B, no. 7, pp. 2278-2285, July 2012, doi: 10.1587/transcom.E95.B.2278.
Abstract: More and more mobile devices adopt multi-battery and dynamic voltage scaling policy (DVS) to reduce the energy consumption and extend the battery runtime. However, since the nonlinear characteristics of the multi-battery are not considered, the practical efficiency is not good enough. In order to reduce the energy consumption and extend the battery runtime, this paper proposes an approach based on the battery characteristics to implement the co-optimization of the multi-battery scheduling and dynamic voltage scaling on multi-battery powered systems. In this work, considering the nonlinear discharging characteristics of the existing batteries, we use the Markov process to depict the multi-battery discharging behavior, and build a multi-objective optimal model to denote the energy consumption and battery states, then propose a binary tree based algorithm to solve this model. By means of this method, we get an optimal and applicable scheme about multi-battery scheduling and dynamic voltage scaling. Experimental results show that this approach achieves an average improvement in battery runtime of 17.5% over the current methods in physical implementation.
URL: https://global.ieice.org/en_transactions/communications/10.1587/transcom.E95.B.2278/_p
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@ARTICLE{e95-b_7_2278,
author={Peng OUYANG, Shouyi YIN, Leibo LIU, Shaojun WEI, },
journal={IEICE TRANSACTIONS on Communications},
title={Multi-Battery Scheduling for Battery-Powered DVS Systems},
year={2012},
volume={E95-B},
number={7},
pages={2278-2285},
abstract={More and more mobile devices adopt multi-battery and dynamic voltage scaling policy (DVS) to reduce the energy consumption and extend the battery runtime. However, since the nonlinear characteristics of the multi-battery are not considered, the practical efficiency is not good enough. In order to reduce the energy consumption and extend the battery runtime, this paper proposes an approach based on the battery characteristics to implement the co-optimization of the multi-battery scheduling and dynamic voltage scaling on multi-battery powered systems. In this work, considering the nonlinear discharging characteristics of the existing batteries, we use the Markov process to depict the multi-battery discharging behavior, and build a multi-objective optimal model to denote the energy consumption and battery states, then propose a binary tree based algorithm to solve this model. By means of this method, we get an optimal and applicable scheme about multi-battery scheduling and dynamic voltage scaling. Experimental results show that this approach achieves an average improvement in battery runtime of 17.5% over the current methods in physical implementation.},
keywords={},
doi={10.1587/transcom.E95.B.2278},
ISSN={1745-1345},
month={July},}
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TY - JOUR
TI - Multi-Battery Scheduling for Battery-Powered DVS Systems
T2 - IEICE TRANSACTIONS on Communications
SP - 2278
EP - 2285
AU - Peng OUYANG
AU - Shouyi YIN
AU - Leibo LIU
AU - Shaojun WEI
PY - 2012
DO - 10.1587/transcom.E95.B.2278
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E95-B
IS - 7
JA - IEICE TRANSACTIONS on Communications
Y1 - July 2012
AB - More and more mobile devices adopt multi-battery and dynamic voltage scaling policy (DVS) to reduce the energy consumption and extend the battery runtime. However, since the nonlinear characteristics of the multi-battery are not considered, the practical efficiency is not good enough. In order to reduce the energy consumption and extend the battery runtime, this paper proposes an approach based on the battery characteristics to implement the co-optimization of the multi-battery scheduling and dynamic voltage scaling on multi-battery powered systems. In this work, considering the nonlinear discharging characteristics of the existing batteries, we use the Markov process to depict the multi-battery discharging behavior, and build a multi-objective optimal model to denote the energy consumption and battery states, then propose a binary tree based algorithm to solve this model. By means of this method, we get an optimal and applicable scheme about multi-battery scheduling and dynamic voltage scaling. Experimental results show that this approach achieves an average improvement in battery runtime of 17.5% over the current methods in physical implementation.
ER -
English
