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Data Driven Performance Evaluation of Wireless Sensor Networks

Wireless Sensor Networks are presented as devices for signal sampling and reconstruction. Within this framework, the qualitative and quantitative influence of (i) signal granularity, (ii) spatial distribution of sensors, (iii) sensors clustering, and (iv) signal reconstruction procedure are assessed...

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Detalles Bibliográficos
Autores principales: Frery, Alejandro C., Ramos, Heitor S., Alencar-Neto, José, Nakamura, Eduardo, Loureiro, Antonio A. F.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Molecular Diversity Preservation International (MDPI) 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3264473/
https://www.ncbi.nlm.nih.gov/pubmed/22294920
http://dx.doi.org/10.3390/s100302150
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author Frery, Alejandro C.
Ramos, Heitor S.
Alencar-Neto, José
Nakamura, Eduardo
Loureiro, Antonio A. F.
author_facet Frery, Alejandro C.
Ramos, Heitor S.
Alencar-Neto, José
Nakamura, Eduardo
Loureiro, Antonio A. F.
author_sort Frery, Alejandro C.
collection PubMed
description Wireless Sensor Networks are presented as devices for signal sampling and reconstruction. Within this framework, the qualitative and quantitative influence of (i) signal granularity, (ii) spatial distribution of sensors, (iii) sensors clustering, and (iv) signal reconstruction procedure are assessed. This is done by defining an error metric and performing a Monte Carlo experiment. It is shown that all these factors have significant impact on the quality of the reconstructed signal. The extent of such impact is quantitatively assessed.
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spelling pubmed-32644732012-01-31 Data Driven Performance Evaluation of Wireless Sensor Networks Frery, Alejandro C. Ramos, Heitor S. Alencar-Neto, José Nakamura, Eduardo Loureiro, Antonio A. F. Sensors (Basel) Article Wireless Sensor Networks are presented as devices for signal sampling and reconstruction. Within this framework, the qualitative and quantitative influence of (i) signal granularity, (ii) spatial distribution of sensors, (iii) sensors clustering, and (iv) signal reconstruction procedure are assessed. This is done by defining an error metric and performing a Monte Carlo experiment. It is shown that all these factors have significant impact on the quality of the reconstructed signal. The extent of such impact is quantitatively assessed. Molecular Diversity Preservation International (MDPI) 2010-03-16 /pmc/articles/PMC3264473/ /pubmed/22294920 http://dx.doi.org/10.3390/s100302150 Text en © 2010 by the authors; licensee Molecular Diversity Preservation International, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/).
spellingShingle Article
Frery, Alejandro C.
Ramos, Heitor S.
Alencar-Neto, José
Nakamura, Eduardo
Loureiro, Antonio A. F.
Data Driven Performance Evaluation of Wireless Sensor Networks
title Data Driven Performance Evaluation of Wireless Sensor Networks
title_full Data Driven Performance Evaluation of Wireless Sensor Networks
title_fullStr Data Driven Performance Evaluation of Wireless Sensor Networks
title_full_unstemmed Data Driven Performance Evaluation of Wireless Sensor Networks
title_short Data Driven Performance Evaluation of Wireless Sensor Networks
title_sort data driven performance evaluation of wireless sensor networks
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3264473/
https://www.ncbi.nlm.nih.gov/pubmed/22294920
http://dx.doi.org/10.3390/s100302150
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