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WSNs Data Acquisition by Combining Hierarchical Routing Method and Compressive Sensing

We address the problem of data acquisition in large distributed wireless sensor networks (WSNs). We propose a method for data acquisition using the hierarchical routing method and compressive sensing for WSNs. Only a few samples are needed to recover the original signal with high probability since s...

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Detalles Bibliográficos
Autores principales: Zou, Zhiqiang, Hu, Cunchen, Zhang, Fei, Zhao, Hao, Shen, Shu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4208198/
https://www.ncbi.nlm.nih.gov/pubmed/25207873
http://dx.doi.org/10.3390/s140916766
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author Zou, Zhiqiang
Hu, Cunchen
Zhang, Fei
Zhao, Hao
Shen, Shu
author_facet Zou, Zhiqiang
Hu, Cunchen
Zhang, Fei
Zhao, Hao
Shen, Shu
author_sort Zou, Zhiqiang
collection PubMed
description We address the problem of data acquisition in large distributed wireless sensor networks (WSNs). We propose a method for data acquisition using the hierarchical routing method and compressive sensing for WSNs. Only a few samples are needed to recover the original signal with high probability since sparse representation technology is exploited to capture the similarities and differences of the original signal. To collect samples effectively in WSNs, a framework for the use of the hierarchical routing method and compressive sensing is proposed, using a randomized rotation of cluster-heads to evenly distribute the energy load among the sensors in the network. Furthermore, L1-minimization and Bayesian compressed sensing are used to approximate the recovery of the original signal from the smaller number of samples with a lower signal reconstruction error. We also give an extensive validation regarding coherence, compression rate, and lifetime, based on an analysis of the theory and experiments in the environment with real world signals. The results show that our solution is effective in a large distributed network, especially for energy constrained WSNs.
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spelling pubmed-42081982014-10-24 WSNs Data Acquisition by Combining Hierarchical Routing Method and Compressive Sensing Zou, Zhiqiang Hu, Cunchen Zhang, Fei Zhao, Hao Shen, Shu Sensors (Basel) Article We address the problem of data acquisition in large distributed wireless sensor networks (WSNs). We propose a method for data acquisition using the hierarchical routing method and compressive sensing for WSNs. Only a few samples are needed to recover the original signal with high probability since sparse representation technology is exploited to capture the similarities and differences of the original signal. To collect samples effectively in WSNs, a framework for the use of the hierarchical routing method and compressive sensing is proposed, using a randomized rotation of cluster-heads to evenly distribute the energy load among the sensors in the network. Furthermore, L1-minimization and Bayesian compressed sensing are used to approximate the recovery of the original signal from the smaller number of samples with a lower signal reconstruction error. We also give an extensive validation regarding coherence, compression rate, and lifetime, based on an analysis of the theory and experiments in the environment with real world signals. The results show that our solution is effective in a large distributed network, especially for energy constrained WSNs. MDPI 2014-09-09 /pmc/articles/PMC4208198/ /pubmed/25207873 http://dx.doi.org/10.3390/s140916766 Text en © 2014 by the authors; licensee MDPI, 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
Zou, Zhiqiang
Hu, Cunchen
Zhang, Fei
Zhao, Hao
Shen, Shu
WSNs Data Acquisition by Combining Hierarchical Routing Method and Compressive Sensing
title WSNs Data Acquisition by Combining Hierarchical Routing Method and Compressive Sensing
title_full WSNs Data Acquisition by Combining Hierarchical Routing Method and Compressive Sensing
title_fullStr WSNs Data Acquisition by Combining Hierarchical Routing Method and Compressive Sensing
title_full_unstemmed WSNs Data Acquisition by Combining Hierarchical Routing Method and Compressive Sensing
title_short WSNs Data Acquisition by Combining Hierarchical Routing Method and Compressive Sensing
title_sort wsns data acquisition by combining hierarchical routing method and compressive sensing
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4208198/
https://www.ncbi.nlm.nih.gov/pubmed/25207873
http://dx.doi.org/10.3390/s140916766
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