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Sensors 2016, 16(4), 448; doi:10.3390/s16040448

An Energy Aware Adaptive Sampling Algorithm for Energy Harvesting WSN with Energy Hungry Sensors

1
Department of Electrical and Electronic Engineering, University College Cork, College Road, Cork T12 YN60, Ireland
2
MaRine Renewable Energy Ireland (MaREI), Environmental Research Institute, University College Cork, College Road, Cork T12 YN60, Ireland
3
Department of Information Technology and Electrical Engineering, ETH Zurich, Zürich 8092, Switzerland
4
Department of Electrical, Electronic and Information Engineering (DEI), University of Bologna, Bologna 40126, Italy
5
Dynamical Systems and Risk Laboratory, School of Engineering, University College Cork, College Road, Cork T12 YN60, Ireland
These authors contributed equally to this work.
*
Author to whom correspondence should be addressed.
Academic Editor: Leonhard M. Reindl
Received: 4 February 2016 / Revised: 18 March 2016 / Accepted: 22 March 2016 / Published: 28 March 2016
(This article belongs to the Section Sensor Networks)
View Full-Text   |   Download PDF [1865 KB, uploaded 28 March 2016]   |  

Abstract

Wireless sensor nodes have a limited power budget, though they are often expected to be functional in the field once deployed for extended periods of time. Therefore, minimization of energy consumption and energy harvesting technology in Wireless Sensor Networks (WSN) are key tools for maximizing network lifetime, and achieving self-sustainability. This paper proposes an energy aware Adaptive Sampling Algorithm (ASA) for WSN with power hungry sensors and harvesting capabilities, an energy management technique that can be implemented on any WSN platform with enough processing power to execute the proposed algorithm. An existing state-of-the-art ASA developed for wireless sensor networks with power hungry sensors is optimized and enhanced to adapt the sampling frequency according to the available energy of the node. The proposed algorithm is evaluated using two in-field testbeds that are supplied by two different energy harvesting sources (solar and wind). Simulation and comparison between the state-of-the-art ASA and the proposed energy aware ASA (EASA) in terms of energy durability are carried out using in-field measured harvested energy (using both wind and solar sources) and power hungry sensors (ultrasonic wind sensor and gas sensors). The simulation results demonstrate that using ASA in combination with an energy aware function on the nodes can drastically increase the lifetime of a WSN node and enable self-sustainability. In fact, the proposed EASA in conjunction with energy harvesting capability can lead towards perpetual WSN operation and significantly outperform the state-of-the-art ASA. View Full-Text
Keywords: adaptive sampling; energy harvesting; energy management; power hungry sensors; solar energy harvesting; wind energy harvesting; WSN adaptive sampling; energy harvesting; energy management; power hungry sensors; solar energy harvesting; wind energy harvesting; WSN
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Srbinovski, B.; Magno, M.; Edwards-Murphy, F.; Pakrashi, V.; Popovici, E. An Energy Aware Adaptive Sampling Algorithm for Energy Harvesting WSN with Energy Hungry Sensors. Sensors 2016, 16, 448.

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