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dc.contributor.author
Srbinovski, Bruno
dc.contributor.author
Magno, Michele
dc.contributor.author
Edwards Murphy, Fiona
dc.contributor.author
Pakrashi, Vikram
dc.contributor.author
Popovici, Emanuel
dc.date.accessioned
2019-06-13T16:08:51Z
dc.date.available
2017-06-12T03:53:27Z
dc.date.available
2019-06-13T16:08:51Z
dc.date.issued
2016-04
dc.identifier.issn
1424-8220
dc.identifier.other
10.3390/s16040448
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/114945
dc.identifier.doi
10.3929/ethz-b-000114945
dc.description.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.
en_US
dc.format
application/pdf
en_US
dc.language.iso
en
en_US
dc.publisher
MDPI
en_US
dc.rights.uri
http://creativecommons.org/licenses/by/4.0/
dc.subject
Adaptive sampling
en_US
dc.subject
Energy harvesting
en_US
dc.subject
Energy management
en_US
dc.subject
Power hungry sensors
en_US
dc.subject
Solar energy harvesting
en_US
dc.subject
Wind energy harvesting
en_US
dc.subject
WSN
en_US
dc.title
An Energy Aware Adaptive Sampling Algorithm for Energy Harvesting WSN with Energy Hungry Sensors
en_US
dc.type
Journal Article
dc.rights.license
Creative Commons Attribution 4.0 International
dc.date.published
2016-03-28
ethz.journal.title
Sensors
ethz.journal.volume
16
en_US
ethz.journal.issue
4
en_US
ethz.pages.start
448
en_US
ethz.size
19 p.
en_US
ethz.version.deposit
publishedVersion
en_US
ethz.identifier.wos
ethz.identifier.scopus
ethz.identifier.nebis
005634210
ethz.publication.place
Basel
en_US
ethz.publication.status
published
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02140 - Dep. Inf.technologie und Elektrotechnik / Dep. of Inform.Technol. Electrical Eng.::02636 - Institut für Integrierte Systeme / Integrated Systems Laboratory::03996 - Benini, Luca / Benini, Luca
en_US
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02140 - Dep. Inf.technologie und Elektrotechnik / Dep. of Inform.Technol. Electrical Eng.::02636 - Institut für Integrierte Systeme / Integrated Systems Laboratory::03996 - Benini, Luca / Benini, Luca
ethz.date.deposited
2017-06-12T03:59:11Z
ethz.source
ECIT
ethz.identifier.importid
imp5936544998eec32978
ethz.ecitpid
pub:176754
ethz.eth
yes
en_US
ethz.availability
Open access
en_US
ethz.rosetta.installDate
2017-07-15T04:39:32Z
ethz.rosetta.lastUpdated
2019-06-13T16:09:00Z
ethz.rosetta.versionExported
true
ethz.COinS
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