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A grid-shaped cellular modeling approach for wireless sensor networks

WSN (Wireless Sensor Network) applications have been widely used in recent years. We introduce a new method for modeling WSN, based on the specification of the WSN using the Cell-Discrete-Event Systems Specification (DEVS) formalism: the space is partitioned into cells where each cell can be conside...

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Detalles Bibliográficos
Autores principales: Al-Zoubi, Khaldoon, Wainer, Gabriel A
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9445403/
https://www.ncbi.nlm.nih.gov/pubmed/36089988
http://dx.doi.org/10.1177/00375497221093379
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author Al-Zoubi, Khaldoon
Wainer, Gabriel A
author_facet Al-Zoubi, Khaldoon
Wainer, Gabriel A
author_sort Al-Zoubi, Khaldoon
collection PubMed
description WSN (Wireless Sensor Network) applications have been widely used in recent years. We introduce a new method for modeling WSN, based on the specification of the WSN using the Cell-Discrete-Event Systems Specification (DEVS) formalism: the space is partitioned into cells where each cell can be considered a sensor, an obstacle, or anything of a behavior with defined rules. This model is then converted automatically into DEVS model at runtime. We present two case studies analyzing the use of energy in WSN member nodes, which have impact on prolonging the overall network lifetime. We study to analyze energy consumption related to routing and data transmission at the node level, and topology residual energy control methods at the cluster level (i.e. group of sensors) level. The goal is to show how these spatial modeling methods can be used for building WSN models in a simple but efficient fashion.
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spelling pubmed-94454032022-09-07 A grid-shaped cellular modeling approach for wireless sensor networks Al-Zoubi, Khaldoon Wainer, Gabriel A Simulation Methodology WSN (Wireless Sensor Network) applications have been widely used in recent years. We introduce a new method for modeling WSN, based on the specification of the WSN using the Cell-Discrete-Event Systems Specification (DEVS) formalism: the space is partitioned into cells where each cell can be considered a sensor, an obstacle, or anything of a behavior with defined rules. This model is then converted automatically into DEVS model at runtime. We present two case studies analyzing the use of energy in WSN member nodes, which have impact on prolonging the overall network lifetime. We study to analyze energy consumption related to routing and data transmission at the node level, and topology residual energy control methods at the cluster level (i.e. group of sensors) level. The goal is to show how these spatial modeling methods can be used for building WSN models in a simple but efficient fashion. SAGE Publications 2022-05-04 2022-10 /pmc/articles/PMC9445403/ /pubmed/36089988 http://dx.doi.org/10.1177/00375497221093379 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by-nc/4.0/This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage).
spellingShingle Methodology
Al-Zoubi, Khaldoon
Wainer, Gabriel A
A grid-shaped cellular modeling approach for wireless sensor networks
title A grid-shaped cellular modeling approach for wireless sensor networks
title_full A grid-shaped cellular modeling approach for wireless sensor networks
title_fullStr A grid-shaped cellular modeling approach for wireless sensor networks
title_full_unstemmed A grid-shaped cellular modeling approach for wireless sensor networks
title_short A grid-shaped cellular modeling approach for wireless sensor networks
title_sort grid-shaped cellular modeling approach for wireless sensor networks
topic Methodology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9445403/
https://www.ncbi.nlm.nih.gov/pubmed/36089988
http://dx.doi.org/10.1177/00375497221093379
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