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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...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Molecular Diversity Preservation International (MDPI)
2010
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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. |
format | Online Article Text |
id | pubmed-3264473 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2010 |
publisher | Molecular Diversity Preservation International (MDPI) |
record_format | MEDLINE/PubMed |
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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