title: An Energy Aware Adaptive Sampling Algorithm for Energy Harvesting WSN with Energy Hungry Sensors.
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.
authors.affiliation: Department of Electrical and Electronic Engineering, University College Cork, College Road, Cork T12 YN60, Ireland. b.srbinovski@ue.ucc.ie.|MaRine Renewable Energy Ireland (MaREI), Environmental Research Institute, University College Cork, College Road, Cork T12 YN60, Ireland. b.srbinovski@ue.ucc.ie.
authors.forename: Bruno
authors.initials: B
authors.lastname: Srbinovski
authors.affiliation: Department of Information Technology and Electrical Engineering, ETH Zurich, Zürich 8092, Switzerland. magnom@iis.ee.ethz.ch.|Department of Electrical, Electronic and Information Engineering (DEI), University of Bologna, Bologna 40126, Italy. magnom@iis.ee.ethz.ch.
authors.forename: Michele
authors.initials: M
authors.lastname: Magno
authors.affiliation: Department of Electrical and Electronic Engineering, University College Cork, College Road, Cork T12 YN60, Ireland. f.edwardsmurphy@umail.ucc.ie.
authors.forename: Fiona
authors.initials: F
authors.lastname: Edwards-Murphy
authors.affiliation: MaRine Renewable Energy Ireland (MaREI), Environmental Research Institute, University College Cork, College Road, Cork T12 YN60, Ireland. V.Pakrashi@ucc.ie.|Dynamical Systems and Risk Laboratory, School of Engineering, University College Cork, College Road, Cork T12 YN60, Ireland. V.Pakrashi@ucc.ie.
authors.forename: Vikram
authors.initials: V
authors.lastname: Pakrashi
authors.affiliation: Department of Electrical and Electronic Engineering, University College Cork, College Road, Cork T12 YN60, Ireland. e.popovici@ucc.ie.
authors.forename: Emanuel
authors.initials: E
authors.lastname: Popovici
keywords: WSN; adaptive sampling; energy harvesting; energy management; power hungry sensors; solar energy harvesting; wind energy harvesting