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Design of Self-sustainable Wireless Sensor Networks with Energy Harvesting and Wireless Charging

Design of Self-sustainable Wireless Sensor Networks with Energy Harvesting and Wireless Charging Energy provisioning plays a key role in the sustainable operations of Wireless Sensor Networks (WSNs). Recent efforts deploy multi-source energy harvesting sensors to utilize ambient energy. Meanwhile, wireless charging is a reliable energy source not affected by spatial-temporal ambient dynamics. This article integrates multiple energy provisioning strategies and adaptive adjustment to accomplish self-sustainability under complex weather conditions. We design and optimize a three-tier framework with the first two tiers focusing on the planning problems of sensors with various types and distributed energy storage powered by environmental energy. Then we schedule the Mobile Chargers (MC) between different charging activities and propose an efficient, 4-factor approximation algorithm. Finally, we adaptively adjust the algorithms to capture real-time energy profiles and jointly optimize those correlated modules. Our extensive simulations demonstrate significant improvement of network lifetime (), increase of harvested energy (15%), reduction of network cost (30%), and the charging capability of MC by 100%. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png ACM Transactions on Sensor Networks (TOSN) Association for Computing Machinery

Design of Self-sustainable Wireless Sensor Networks with Energy Harvesting and Wireless Charging

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References (82)

Publisher
Association for Computing Machinery
Copyright
Copyright © 2021 Association for Computing Machinery.
ISSN
1550-4859
eISSN
1550-4867
DOI
10.1145/3459081
Publisher site
See Article on Publisher Site

Abstract

Energy provisioning plays a key role in the sustainable operations of Wireless Sensor Networks (WSNs). Recent efforts deploy multi-source energy harvesting sensors to utilize ambient energy. Meanwhile, wireless charging is a reliable energy source not affected by spatial-temporal ambient dynamics. This article integrates multiple energy provisioning strategies and adaptive adjustment to accomplish self-sustainability under complex weather conditions. We design and optimize a three-tier framework with the first two tiers focusing on the planning problems of sensors with various types and distributed energy storage powered by environmental energy. Then we schedule the Mobile Chargers (MC) between different charging activities and propose an efficient, 4-factor approximation algorithm. Finally, we adaptively adjust the algorithms to capture real-time energy profiles and jointly optimize those correlated modules. Our extensive simulations demonstrate significant improvement of network lifetime (), increase of harvested energy (15%), reduction of network cost (30%), and the charging capability of MC by 100%.

Journal

ACM Transactions on Sensor Networks (TOSN)Association for Computing Machinery

Published: Jul 16, 2021

Keywords: Multi-source energy harvesting

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