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Campo DC | Valor | Lengua/Idioma |
---|---|---|
dc.contributor.author | Gindullina, Elvina | - |
dc.contributor.author | Badia, Leonardo | - |
dc.contributor.author | Vilajosana, Xavier | - |
dc.date.accessioned | 2023-09-29T07:41:32Z | - |
dc.date.available | 2023-09-29T07:41:32Z | - |
dc.date.issued | 2019-08-16 | - |
dc.date.issued | 2019-08-16 | - |
dc.identifier.citation | Gindullina, E. [Elvina]. Badia, L. [Leonardo]. Vilajosana, X. [Xavier]. (2020). Energy modeling and adaptive sampling algorithms for energy-harvesting powered nodes with sampling rate limitations. Transactions on Emerging Telecommunications Technologies, 31(3), 1-15. doi: 10.1002/ett.3754 | - |
dc.identifier.issn | 2161-3915MIAR | - |
dc.identifier.uri | http://hdl.handle.net/10609/148971 | - |
dc.description.abstract | This article explores the implementation of different sampling strategies for a practical energy-harvesting wireless device (sensor node) powered by a rechargeable battery. We look for a realistic yet effective sampling strategy that prevents packet delivery failures, which is simple enough to be implemented in low-complexity hardware. The article proposes methods that balance erratic energy arrivals and include advantages of dynamic data-driven approaches based on historical data. Due to the industrial requirements in terms of mini- mum acceptable sampling frequency, we also integrate sampling rate limits and verify the proposed methods. To do so, we simulated the operation of an indus- trial data logger powered with a solar panel relying on the enhanced state of the model for battery charging. Finally, the proposed methods are compared based on energy consumption over a year and the amount of packet delivery failures, thus showing how some modifications of available strategies achieve satisfactory performance in this sense. | en |
dc.description.abstract | This article explores the implementation of different sampling strategies for a practical energy-harvesting wireless device (sensor node) powered by a rechargeable battery. We look for a realistic yet effective sampling strategy that prevents packet delivery failures, which is simple enough to be implemented in low-complexity hardware. The article proposes methods that balance erratic energy arrivals and include advantages of dynamic data-driven approaches based on historical data. Due to the industrial requirements in terms of mini- mum acceptable sampling frequency, we also integrate sampling rate limits and verify the proposed methods. To do so, we simulated the operation of an indus- trial data logger powered with a solar panel relying on the enhanced state of the model for battery charging. Finally, the proposed methods are compared based on energy consumption over a year and the amount of packet delivery failures, thus showing how some modifications of available strategies achieve satisfactory performance in this sense. | en |
dc.format.mimetype | application/pdf | ca |
dc.language.iso | eng | ca |
dc.publisher | Wiley | ca |
dc.publisher | Wiley | ca |
dc.relation.ispartof | Transactions on Emerging Telecommunications Technologies, 2019, 31(3), 1-15. | - |
dc.relation.uri | https://doi.org/10.1002/ett.3754 | - |
dc.rights | © 2019 John Wiley & Sons, Ltd. | - |
dc.title | Energy modeling and adaptive sampling algorithms for energy-harvesting powered nodes with sampling rate limitations | ca |
dc.type | info:eu-repo/semantics/article | ca |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | - |
dc.identifier.doi | https://doi.org/10.1002/ett.3754 | - |
dc.gir.id | AR/0000007353 | - |
dc.type.version | info:eu-repo/semantics/acceptedVersion | - |
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Fichero | Descripción | Tamaño | Formato | |
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Elvina_Energy_ETT_merged.pdf | 1,35 MB | Adobe PDF | ![]() Visualizar/Abrir |
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