research-article

Maximizing Quality of Coverage under Connectivity Constraints in Solar-Powered Active Wireless Sensor Networks

Authors:

Benjamin Gaudette,

Vinay Hanumaiah,

Sarma VrudhulaAuthors Info & Claims

ACM Transactions on Sensor Networks (TOSN), Volume 10, Issue 4

Article No.: 59, Pages 1 - 27

https://doi.org/10.1145/2594792

Published: 01 June 2014 Publication History

Abstract

Energy harvesting is a promising solution for reducing network maintenance and the overhead of replacing chemical batteries in sensor networks. In this article, problems related to controlling an active wireless sensor network comprised of nodes powered by both rechargeable batteries and solar energy are investigated. The objective of this control is to maximize the network's Quality of Coverage (QoC), defined as the minimum number of targets that can be covered by the network over a 24-hour period. Assuming a time-varying solar profile, the underlying problem is to optimally control the sensing range of each sensor so as to maximize the QoC. The problem is further constrained by requiring all active sensors to report any sensed data to a centralized base station, making connectivity a key factor in sensor management. Implicit in the solution is the allocation of solar energy during the day to sensing tasks and recharging of the battery so that a minimum coverage is guaranteed at all times. The problem turns out to be a nonlinear optimal control problem of high complexity. By exploiting the particular structure of the problem, we present a novel method for determining near-optimal sensing radii and routing paths as a series of quasiconvex (unimodal) optimization problems. The runtime of the proposed solution is 60X less than the standard optimal control method based on dynamic programming, while the worst-case error is less than 8%. The proposed method is scalable to large networks consisting of hundreds of sensors and targets. Several insights in the design of energy-harvesting networks are provided.

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https://doi.org/10.1007/s12652-024-04781-3
Li JJiang CWang JXu TXiao W(2023)Mobile Charging Sequence Scheduling for Optimal Sensing Coverage in Wireless Rechargeable Sensor NetworksApplied Sciences10.3390/app1305284013:5(2840)Online publication date: 22-Feb-2023
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Li CChin KYang C(2021)Complete Target Coverage in Radio Frequency and Solar-Powered Sensor NetworksIEEE Systems Journal10.1109/JSYST.2020.299730015:3(3609-3619)Online publication date: Sep-2021
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Maximizing Quality of Coverage under Connectivity Constraints in Solar-Powered Active Wireless Sensor Networks

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Published In

cover image ACM Transactions on Sensor Networks

ACM Transactions on Sensor Networks Volume 10, Issue 4

June 2014

480 pages

ISSN:1550-4859

EISSN:1550-4867

DOI:10.1145/2633905

Issue’s Table of Contents

Copyright © 2014 ACM.

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Association for Computing Machinery

New York, NY, United States

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ACM Journals for the Design of Smart and Connected Systems

Publication History

Published: 01 June 2014

Accepted: 01 August 2013

Revised: 01 July 2013

Received: 01 October 2012

Published in TOSN Volume 10, Issue 4

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Division of Computer and Network Systems
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Stardust Foundation

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Cited By

Li JWang HXiao W(2024)A reinforcement learning based mobile charging sequence scheduling algorithm for optimal sensing coverage in wireless rechargeable sensor networksJournal of Ambient Intelligence and Humanized Computing10.1007/s12652-024-04781-315:6(2869-2881)Online publication date: 6-Apr-2024
https://doi.org/10.1007/s12652-024-04781-3
Li JJiang CWang JXu TXiao W(2023)Mobile Charging Sequence Scheduling for Optimal Sensing Coverage in Wireless Rechargeable Sensor NetworksApplied Sciences10.3390/app1305284013:5(2840)Online publication date: 22-Feb-2023
https://doi.org/10.3390/app13052840
Li CChin KYang C(2021)Complete Target Coverage in Radio Frequency and Solar-Powered Sensor NetworksIEEE Systems Journal10.1109/JSYST.2020.299730015:3(3609-3619)Online publication date: Sep-2021
https://doi.org/10.1109/JSYST.2020.2997300
Liao WDande BChang CRoy D(2020)MMQT: Maximizing the Monitoring Quality for Targets Based on Probabilistic Sensing Model in Rechargeable Wireless Sensor NetworksIEEE Access10.1109/ACCESS.2020.29891998(77073-77088)Online publication date: 2020
https://doi.org/10.1109/ACCESS.2020.2989199
Jia RZhang JLiu XLiu PFu LWang X(2019)Optimal Rate Control for Energy-Harvesting Systems with Random Data and Energy ArrivalsACM Transactions on Sensor Networks10.1145/329353515:1(1-30)Online publication date: 10-Feb-2019
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Dong ZChang CChen GChang IXu P(2019)Maximizing Surveillance Quality of Boundary Curve in Solar-Powered Wireless Sensor NetworksIEEE Access10.1109/ACCESS.2019.29222337(77771-77785)Online publication date: 2019
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Wang CLi JYang YYe F(2018)Combining Solar Energy Harvesting with Wireless Charging for Hybrid Wireless Sensor NetworksIEEE Transactions on Mobile Computing10.1109/TMC.2017.273297917:3(560-576)Online publication date: 1-Mar-2018
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Harrison DSeah WRayudu R(2017)Coverage Preservation with Rapid Forwarding in Energy-Harvesting Wireless Sensor Networks for Critical Rare EventsACM Transactions on Embedded Computing Systems10.1145/314096117:2(1-25)Online publication date: 7-Dec-2017
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