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Open AccessArticle

Harvesting-Aware Energy Management for Environmental Monitoring WSN

by James Rodway 1,‡ and Petr Musilek 1,2,*,‡
Department of Electrical and Computer Engineering, University of Alberta, Edmonton, AB T6G 1H9, Canada
Faculty of Electrical Engineering and Computer Science, VŠB-TU Ostrava, 708 33 Ostrava, Czech Republic
Author to whom correspondence should be addressed.
This paper is an extended version of our paper published in Rodway, J.; Musilek, P. Harvesting-aware energy management for environmental monitoring WSN. In Proceedings of the 2016 IEEE 16th International Conference on Environment and Electrical Engineering (EEEIC), Florence, Italy, 7–10 June 2016.
These authors contributed equally to this work.
Academic Editor: Rodolfo Araneo
Energies 2017, 10(5), 607;
Received: 14 February 2017 / Revised: 20 April 2017 / Accepted: 21 April 2017 / Published: 1 May 2017
Wireless sensor networks can be used to collect data in remote locations, especially when energy harvesting is used to extend the lifetime of individual nodes. However, in order to use the collected energy most effectively, its consumption must be managed. In this work, forecasts of diurnal solar energies were made based on measurements of atmospheric pressure. These forecasts were used as part of an adaptive duty cycling scheme for node level energy management. This management was realized with a fuzzy logic controller that has been tuned using differential evolution. Controllers were created using one and two days of energy forecasts, then simulated in software. These controllers outperformed a human-created reference controller by taking more measurements while using less reserve energy during the simulated period. The energy forecasts were comparable to other available methods, while the method of tuning the fuzzy controller improved overall node performance. The combination of the two is a promising method of energy management. View Full-Text
Keywords: wireless sensor networks; energy forecast; differential evolution; energy management wireless sensor networks; energy forecast; differential evolution; energy management
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Rodway, J.; Musilek, P. Harvesting-Aware Energy Management for Environmental Monitoring WSN. Energies 2017, 10, 607.

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