Sensor power scheduling : tradeoff between state estimation quality and power cost

Heng Zhang; Wei Xing Zheng

doi:10.1109/YAC.2017.7967541

Sensor power scheduling : tradeoff between state estimation quality and power cost

Heng Zhang, Wei Xing Zheng

Western Sydney University

Research output: Chapter in Book / Conference Paper › Conference Paper › peer-review

2 Citations (Scopus)

Abstract

![CDATA[This paper is concerned with the sensor power management problem in remote state estimation. An optimization problem is first constructed which minimizes the weighted average sum of the estimation errors and the sensor power costs. Then a Markov decision process (MDP) based method is used to find out the optimal solution. Since the optimal solution cannot be analytically expressed, an approximation of the solution is provided and then a suboptimal transmission strategy is obtained. Finally, a simulation example is presented to demonstrate the effectiveness of the proposed sensor transmission strategy.]]

Original language	English
Title of host publication	Proceedings of the 32nd Youth Academic Annual Conference of Chinese Association of Automation, 19-21 May, 2017, Hefei, China
Publisher	IEEE
Pages	922-927
Number of pages	6
ISBN (Print)	9781538629017
DOIs	https://doi.org/10.1109/YAC.2017.7967541
Publication status	Published - 2017
Event	Youth Academic Annual Conference of Chinese Association of Automation - Duration: 19 May 2017 → …

Conference

Conference	Youth Academic Annual Conference of Chinese Association of Automation
Period	19/05/17 → …

Keywords

Markov processes
estimation theory
power resources

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10.1109/YAC.2017.7967541

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@inproceedings{47a55879e48a4cae857b4f56c259f807,

title = "Sensor power scheduling : tradeoff between state estimation quality and power cost",

abstract = "![CDATA[This paper is concerned with the sensor power management problem in remote state estimation. An optimization problem is first constructed which minimizes the weighted average sum of the estimation errors and the sensor power costs. Then a Markov decision process (MDP) based method is used to find out the optimal solution. Since the optimal solution cannot be analytically expressed, an approximation of the solution is provided and then a suboptimal transmission strategy is obtained. Finally, a simulation example is presented to demonstrate the effectiveness of the proposed sensor transmission strategy.]]",

keywords = "Markov processes, estimation theory, power resources",

author = "Heng Zhang and Zheng, {Wei Xing}",

year = "2017",

doi = "10.1109/YAC.2017.7967541",

language = "English",

isbn = "9781538629017",

pages = "922--927",

booktitle = "Proceedings of the 32nd Youth Academic Annual Conference of Chinese Association of Automation, 19-21 May, 2017, Hefei, China",

publisher = "IEEE",

note = "Youth Academic Annual Conference of Chinese Association of Automation ; Conference date: 19-05-2017",

}

Zhang, H & Zheng, WX 2017, Sensor power scheduling : tradeoff between state estimation quality and power cost. in Proceedings of the 32nd Youth Academic Annual Conference of Chinese Association of Automation, 19-21 May, 2017, Hefei, China. IEEE, pp. 922-927, Youth Academic Annual Conference of Chinese Association of Automation, 19/05/17. https://doi.org/10.1109/YAC.2017.7967541

TY - GEN

T1 - Sensor power scheduling : tradeoff between state estimation quality and power cost

AU - Zhang, Heng

AU - Zheng, Wei Xing

PY - 2017

Y1 - 2017

N2 - ![CDATA[This paper is concerned with the sensor power management problem in remote state estimation. An optimization problem is first constructed which minimizes the weighted average sum of the estimation errors and the sensor power costs. Then a Markov decision process (MDP) based method is used to find out the optimal solution. Since the optimal solution cannot be analytically expressed, an approximation of the solution is provided and then a suboptimal transmission strategy is obtained. Finally, a simulation example is presented to demonstrate the effectiveness of the proposed sensor transmission strategy.]]

AB - ![CDATA[This paper is concerned with the sensor power management problem in remote state estimation. An optimization problem is first constructed which minimizes the weighted average sum of the estimation errors and the sensor power costs. Then a Markov decision process (MDP) based method is used to find out the optimal solution. Since the optimal solution cannot be analytically expressed, an approximation of the solution is provided and then a suboptimal transmission strategy is obtained. Finally, a simulation example is presented to demonstrate the effectiveness of the proposed sensor transmission strategy.]]

KW - Markov processes

KW - estimation theory

KW - power resources

UR - http://handle.westernsydney.edu.au:8081/1959.7/uws:46415

U2 - 10.1109/YAC.2017.7967541

DO - 10.1109/YAC.2017.7967541

M3 - Conference Paper

SN - 9781538629017

SP - 922

EP - 927

BT - Proceedings of the 32nd Youth Academic Annual Conference of Chinese Association of Automation, 19-21 May, 2017, Hefei, China

PB - IEEE

T2 - Youth Academic Annual Conference of Chinese Association of Automation

Y2 - 19 May 2017

ER -

Sensor power scheduling : tradeoff between state estimation quality and power cost

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