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A Subspace Approach to Sparse Sampling Based Data Gathering in Wireless Sensor Networks
Data gathering is an essential concern in Wireless Sensor Networks (WSNs). This paper proposes an efficient data gathering method in clustered WSNs based on sparse sampling to reduce energy consumption and prolong the network lifetime. For data gathering scheme, we propose a method that can collect...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7070245/ https://www.ncbi.nlm.nih.gov/pubmed/32059454 http://dx.doi.org/10.3390/s20040985 |
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author | He, Jingfei Zhang, Xiaoyue Zhou, Yatong Maibvisira, Miriam |
author_facet | He, Jingfei Zhang, Xiaoyue Zhou, Yatong Maibvisira, Miriam |
author_sort | He, Jingfei |
collection | PubMed |
description | Data gathering is an essential concern in Wireless Sensor Networks (WSNs). This paper proposes an efficient data gathering method in clustered WSNs based on sparse sampling to reduce energy consumption and prolong the network lifetime. For data gathering scheme, we propose a method that can collect sparse sampled data in each time slot with a fixed percent of nodes remaining in sleep mode. For data reconstruction, a subspace approach is proposed to enforce an explicit low-rank constraint for data reconstruction from sparse sampled data. Subspace representing spatial distributions of the WSNs data can be estimated from previous reconstructed data. Incorporating total variation constraint, the proposed reconstruction method reconstructs current time slot data efficiently. The results of experiments indicate that the proposed method can reduce the energy consumption and prolong the network lifetime with satisfying recovery accuracy. |
format | Online Article Text |
id | pubmed-7070245 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-70702452020-03-19 A Subspace Approach to Sparse Sampling Based Data Gathering in Wireless Sensor Networks He, Jingfei Zhang, Xiaoyue Zhou, Yatong Maibvisira, Miriam Sensors (Basel) Article Data gathering is an essential concern in Wireless Sensor Networks (WSNs). This paper proposes an efficient data gathering method in clustered WSNs based on sparse sampling to reduce energy consumption and prolong the network lifetime. For data gathering scheme, we propose a method that can collect sparse sampled data in each time slot with a fixed percent of nodes remaining in sleep mode. For data reconstruction, a subspace approach is proposed to enforce an explicit low-rank constraint for data reconstruction from sparse sampled data. Subspace representing spatial distributions of the WSNs data can be estimated from previous reconstructed data. Incorporating total variation constraint, the proposed reconstruction method reconstructs current time slot data efficiently. The results of experiments indicate that the proposed method can reduce the energy consumption and prolong the network lifetime with satisfying recovery accuracy. MDPI 2020-02-12 /pmc/articles/PMC7070245/ /pubmed/32059454 http://dx.doi.org/10.3390/s20040985 Text en © 2020 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 (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article He, Jingfei Zhang, Xiaoyue Zhou, Yatong Maibvisira, Miriam A Subspace Approach to Sparse Sampling Based Data Gathering in Wireless Sensor Networks |
title | A Subspace Approach to Sparse Sampling Based Data Gathering in Wireless Sensor Networks |
title_full | A Subspace Approach to Sparse Sampling Based Data Gathering in Wireless Sensor Networks |
title_fullStr | A Subspace Approach to Sparse Sampling Based Data Gathering in Wireless Sensor Networks |
title_full_unstemmed | A Subspace Approach to Sparse Sampling Based Data Gathering in Wireless Sensor Networks |
title_short | A Subspace Approach to Sparse Sampling Based Data Gathering in Wireless Sensor Networks |
title_sort | subspace approach to sparse sampling based data gathering in wireless sensor networks |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7070245/ https://www.ncbi.nlm.nih.gov/pubmed/32059454 http://dx.doi.org/10.3390/s20040985 |
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