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Energy-Efficient Industrial Internet of Things Software-Defined Network by Means of the Peano Fractal

The Industrial Internet of Things (IIoT) network generates great economic benefits in processes, system installation, maintenance, reliability, scalability, and interoperability. Wireless sensor networks (WSNs) allow the IIoT network to collect, process, and share data of different parameters among...

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Autores principales: Moreno Escobar, Jesus Jaime, Morales Matamoros, Oswaldo, Lina Reyes, Ixchel, Tejeida-Padilla, Ricardo, Chanona Hernández, Liliana, Posadas Durán, Juan Pablo Francisco
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7288025/
https://www.ncbi.nlm.nih.gov/pubmed/32443435
http://dx.doi.org/10.3390/s20102855
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author Moreno Escobar, Jesus Jaime
Morales Matamoros, Oswaldo
Lina Reyes, Ixchel
Tejeida-Padilla, Ricardo
Chanona Hernández, Liliana
Posadas Durán, Juan Pablo Francisco
author_facet Moreno Escobar, Jesus Jaime
Morales Matamoros, Oswaldo
Lina Reyes, Ixchel
Tejeida-Padilla, Ricardo
Chanona Hernández, Liliana
Posadas Durán, Juan Pablo Francisco
author_sort Moreno Escobar, Jesus Jaime
collection PubMed
description The Industrial Internet of Things (IIoT) network generates great economic benefits in processes, system installation, maintenance, reliability, scalability, and interoperability. Wireless sensor networks (WSNs) allow the IIoT network to collect, process, and share data of different parameters among Industrial IoT sense Node (IISN). ESP8266 are IISNs connected to the Internet by means of a hub to share their information. In this article, a light-diffusion algorithm in WSN to connect all the IISNs is designed, based on the Peano fractal and swarm intelligence, i.e., without using a hub, simply sharing parameters with two adjacent IINSs, assuming that any IISN knows the parameters of the rest of these devices, even if they are not adjacent. We simulated the performance of our algorithm and compared it with other state-of-the-art protocols, finding that our proposal generates a longer lifetime of the IIoT network when few IISNs were connected. Thus, there is a saving-energy of approximately 5% but with 64 nodes there is a saving of more than 20%, because the IIoT network can grow in a [Formula: see text] way and the proposed topology does not impact in a linear way but [Formula: see text] , which balances energy consumption throughout the IIoT network.
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spelling pubmed-72880252020-06-15 Energy-Efficient Industrial Internet of Things Software-Defined Network by Means of the Peano Fractal Moreno Escobar, Jesus Jaime Morales Matamoros, Oswaldo Lina Reyes, Ixchel Tejeida-Padilla, Ricardo Chanona Hernández, Liliana Posadas Durán, Juan Pablo Francisco Sensors (Basel) Article The Industrial Internet of Things (IIoT) network generates great economic benefits in processes, system installation, maintenance, reliability, scalability, and interoperability. Wireless sensor networks (WSNs) allow the IIoT network to collect, process, and share data of different parameters among Industrial IoT sense Node (IISN). ESP8266 are IISNs connected to the Internet by means of a hub to share their information. In this article, a light-diffusion algorithm in WSN to connect all the IISNs is designed, based on the Peano fractal and swarm intelligence, i.e., without using a hub, simply sharing parameters with two adjacent IINSs, assuming that any IISN knows the parameters of the rest of these devices, even if they are not adjacent. We simulated the performance of our algorithm and compared it with other state-of-the-art protocols, finding that our proposal generates a longer lifetime of the IIoT network when few IISNs were connected. Thus, there is a saving-energy of approximately 5% but with 64 nodes there is a saving of more than 20%, because the IIoT network can grow in a [Formula: see text] way and the proposed topology does not impact in a linear way but [Formula: see text] , which balances energy consumption throughout the IIoT network. MDPI 2020-05-18 /pmc/articles/PMC7288025/ /pubmed/32443435 http://dx.doi.org/10.3390/s20102855 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
Moreno Escobar, Jesus Jaime
Morales Matamoros, Oswaldo
Lina Reyes, Ixchel
Tejeida-Padilla, Ricardo
Chanona Hernández, Liliana
Posadas Durán, Juan Pablo Francisco
Energy-Efficient Industrial Internet of Things Software-Defined Network by Means of the Peano Fractal
title Energy-Efficient Industrial Internet of Things Software-Defined Network by Means of the Peano Fractal
title_full Energy-Efficient Industrial Internet of Things Software-Defined Network by Means of the Peano Fractal
title_fullStr Energy-Efficient Industrial Internet of Things Software-Defined Network by Means of the Peano Fractal
title_full_unstemmed Energy-Efficient Industrial Internet of Things Software-Defined Network by Means of the Peano Fractal
title_short Energy-Efficient Industrial Internet of Things Software-Defined Network by Means of the Peano Fractal
title_sort energy-efficient industrial internet of things software-defined network by means of the peano fractal
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7288025/
https://www.ncbi.nlm.nih.gov/pubmed/32443435
http://dx.doi.org/10.3390/s20102855
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