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Cellular Simulation for Distributed Sensing over Complex Terrains
Long-range radio transmissions open new sensor application fields, in particular for environment monitoring. For example, the LoRa radio protocol enables connecting remote sensors at a distance as long as ten kilometers in a line-of-sight. However, the large area covered also brings several difficul...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6068496/ https://www.ncbi.nlm.nih.gov/pubmed/30018279 http://dx.doi.org/10.3390/s18072323 |
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author | Truong, Tuyen Phong Pottier, Bernard Huynh, Hiep Xuan |
author_facet | Truong, Tuyen Phong Pottier, Bernard Huynh, Hiep Xuan |
author_sort | Truong, Tuyen Phong |
collection | PubMed |
description | Long-range radio transmissions open new sensor application fields, in particular for environment monitoring. For example, the LoRa radio protocol enables connecting remote sensors at a distance as long as ten kilometers in a line-of-sight. However, the large area covered also brings several difficulties, such as the placement of sensing devices in regards to topology in geography, or the variability of communication latency. Sensing the environment also carries constraints related to the interest of sensing points in relation to a physical phenomenon. Thus, criteria for designs are evolving a lot from the existing methods, especially in complex terrains. This article describes simulation techniques based on geography analysis to compute long-range radio coverages and radio characteristics in these situations. As radio propagation is just a particular case of physical phenomena, it is shown how a unified approach also allows for characterizing the behavior of potential physical risks. The case of heavy rainfall and flooding is investigated. Geography analysis is achieved using segmentation tools to produce cellular systems which are in turn translated into code for high-performance computations. The paper provides results from practical complex terrain experiments using LoRa, which confirm the accuracy of the simulation, and scheduling characteristics for sample networks. Performance tables are produced for these simulations on current Graphics Processing Units (GPUs). |
format | Online Article Text |
id | pubmed-6068496 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-60684962018-08-07 Cellular Simulation for Distributed Sensing over Complex Terrains Truong, Tuyen Phong Pottier, Bernard Huynh, Hiep Xuan Sensors (Basel) Article Long-range radio transmissions open new sensor application fields, in particular for environment monitoring. For example, the LoRa radio protocol enables connecting remote sensors at a distance as long as ten kilometers in a line-of-sight. However, the large area covered also brings several difficulties, such as the placement of sensing devices in regards to topology in geography, or the variability of communication latency. Sensing the environment also carries constraints related to the interest of sensing points in relation to a physical phenomenon. Thus, criteria for designs are evolving a lot from the existing methods, especially in complex terrains. This article describes simulation techniques based on geography analysis to compute long-range radio coverages and radio characteristics in these situations. As radio propagation is just a particular case of physical phenomena, it is shown how a unified approach also allows for characterizing the behavior of potential physical risks. The case of heavy rainfall and flooding is investigated. Geography analysis is achieved using segmentation tools to produce cellular systems which are in turn translated into code for high-performance computations. The paper provides results from practical complex terrain experiments using LoRa, which confirm the accuracy of the simulation, and scheduling characteristics for sample networks. Performance tables are produced for these simulations on current Graphics Processing Units (GPUs). MDPI 2018-07-17 /pmc/articles/PMC6068496/ /pubmed/30018279 http://dx.doi.org/10.3390/s18072323 Text en © 2018 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 Truong, Tuyen Phong Pottier, Bernard Huynh, Hiep Xuan Cellular Simulation for Distributed Sensing over Complex Terrains |
title | Cellular Simulation for Distributed Sensing over Complex Terrains |
title_full | Cellular Simulation for Distributed Sensing over Complex Terrains |
title_fullStr | Cellular Simulation for Distributed Sensing over Complex Terrains |
title_full_unstemmed | Cellular Simulation for Distributed Sensing over Complex Terrains |
title_short | Cellular Simulation for Distributed Sensing over Complex Terrains |
title_sort | cellular simulation for distributed sensing over complex terrains |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6068496/ https://www.ncbi.nlm.nih.gov/pubmed/30018279 http://dx.doi.org/10.3390/s18072323 |
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