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Responsiveness of the Sensor Network to Alarm Events Based on the Potts Model

The paper aims to present modelling the sensor network operation based on the Potts model. The authors presented own approach based on three states in which each node can be. The change in the state of a given node depends on its current state, the impact of surrounding nodes on it, but also values...

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Detalles Bibliográficos
Autores principales: Paszkiewicz, Andrzej, Węgrzyn, Jan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7731224/
https://www.ncbi.nlm.nih.gov/pubmed/33291354
http://dx.doi.org/10.3390/s20236979
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author Paszkiewicz, Andrzej
Węgrzyn, Jan
author_facet Paszkiewicz, Andrzej
Węgrzyn, Jan
author_sort Paszkiewicz, Andrzej
collection PubMed
description The paper aims to present modelling the sensor network operation based on the Potts model. The authors presented own approach based on three states in which each node can be. The change in the state of a given node depends on its current state, the impact of surrounding nodes on it, but also values of the parameters measured. Therefore, the Hamiltonian was introduced as a dependence of both exceeding the limit value of a measured parameter (corresponding to an alarm event), and the state of the battery powering a given node of a sensor. The simulations of the implemented algorithm based on the adopted model presented in the paper relate to the measurement of temperature by a network of sensors. However, this model is universal and can be applied to examine the behaviour of the sensor infrastructure performing various measurements. Moreover, it may simulate the functioning of the critical network infrastructure or sensor networks and industrial sensors supporting the functioning of Industry 4.0.
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spelling pubmed-77312242020-12-12 Responsiveness of the Sensor Network to Alarm Events Based on the Potts Model Paszkiewicz, Andrzej Węgrzyn, Jan Sensors (Basel) Article The paper aims to present modelling the sensor network operation based on the Potts model. The authors presented own approach based on three states in which each node can be. The change in the state of a given node depends on its current state, the impact of surrounding nodes on it, but also values of the parameters measured. Therefore, the Hamiltonian was introduced as a dependence of both exceeding the limit value of a measured parameter (corresponding to an alarm event), and the state of the battery powering a given node of a sensor. The simulations of the implemented algorithm based on the adopted model presented in the paper relate to the measurement of temperature by a network of sensors. However, this model is universal and can be applied to examine the behaviour of the sensor infrastructure performing various measurements. Moreover, it may simulate the functioning of the critical network infrastructure or sensor networks and industrial sensors supporting the functioning of Industry 4.0. MDPI 2020-12-06 /pmc/articles/PMC7731224/ /pubmed/33291354 http://dx.doi.org/10.3390/s20236979 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
Paszkiewicz, Andrzej
Węgrzyn, Jan
Responsiveness of the Sensor Network to Alarm Events Based on the Potts Model
title Responsiveness of the Sensor Network to Alarm Events Based on the Potts Model
title_full Responsiveness of the Sensor Network to Alarm Events Based on the Potts Model
title_fullStr Responsiveness of the Sensor Network to Alarm Events Based on the Potts Model
title_full_unstemmed Responsiveness of the Sensor Network to Alarm Events Based on the Potts Model
title_short Responsiveness of the Sensor Network to Alarm Events Based on the Potts Model
title_sort responsiveness of the sensor network to alarm events based on the potts model
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7731224/
https://www.ncbi.nlm.nih.gov/pubmed/33291354
http://dx.doi.org/10.3390/s20236979
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