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A Framework to Design the Computational Load Distribution of Wireless Sensor Networks in Power Consumption Constrained Environments

In this paper, we present a work based on the computational load distribution among the homogeneous nodes and the Hub/Sink of Wireless Sensor Networks (WSNs). The main contribution of the paper is an early decision support framework helping WSN designers to take decisions about computational load di...

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Autores principales: Sánchez-Álvarez, David, Linaje, Marino, Rodríguez-Pérez, Francisco-Javier
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5949029/
https://www.ncbi.nlm.nih.gov/pubmed/29570645
http://dx.doi.org/10.3390/s18040954
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author Sánchez-Álvarez, David
Linaje, Marino
Rodríguez-Pérez, Francisco-Javier
author_facet Sánchez-Álvarez, David
Linaje, Marino
Rodríguez-Pérez, Francisco-Javier
author_sort Sánchez-Álvarez, David
collection PubMed
description In this paper, we present a work based on the computational load distribution among the homogeneous nodes and the Hub/Sink of Wireless Sensor Networks (WSNs). The main contribution of the paper is an early decision support framework helping WSN designers to take decisions about computational load distribution for those WSNs where power consumption is a key issue (when we refer to “framework” in this work, we are considering it as a support tool to make decisions where the executive judgment can be included along with the set of mathematical tools of the WSN designer; this work shows the need to include the load distribution as an integral component of the WSN system for making early decisions regarding energy consumption). The framework takes advantage of the idea that balancing sensors nodes and Hub/Sink computational load can lead to improved energy consumption for the whole or at least the battery-powered nodes of the WSN. The approach is not trivial and it takes into account related issues such as the required data distribution, nodes, and Hub/Sink connectivity and availability due to their connectivity features and duty-cycle. For a practical demonstration, the proposed framework is applied to an agriculture case study, a sector very relevant in our region. In this kind of rural context, distances, low costs due to vegetable selling prices and the lack of continuous power supplies may lead to viable or inviable sensing solutions for the farmers. The proposed framework systematize and facilitates WSN designers the required complex calculations taking into account the most relevant variables regarding power consumption, avoiding full/partial/prototype implementations, and measurements of different computational load distribution potential solutions for a specific WSN.
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spelling pubmed-59490292018-05-17 A Framework to Design the Computational Load Distribution of Wireless Sensor Networks in Power Consumption Constrained Environments Sánchez-Álvarez, David Linaje, Marino Rodríguez-Pérez, Francisco-Javier Sensors (Basel) Article In this paper, we present a work based on the computational load distribution among the homogeneous nodes and the Hub/Sink of Wireless Sensor Networks (WSNs). The main contribution of the paper is an early decision support framework helping WSN designers to take decisions about computational load distribution for those WSNs where power consumption is a key issue (when we refer to “framework” in this work, we are considering it as a support tool to make decisions where the executive judgment can be included along with the set of mathematical tools of the WSN designer; this work shows the need to include the load distribution as an integral component of the WSN system for making early decisions regarding energy consumption). The framework takes advantage of the idea that balancing sensors nodes and Hub/Sink computational load can lead to improved energy consumption for the whole or at least the battery-powered nodes of the WSN. The approach is not trivial and it takes into account related issues such as the required data distribution, nodes, and Hub/Sink connectivity and availability due to their connectivity features and duty-cycle. For a practical demonstration, the proposed framework is applied to an agriculture case study, a sector very relevant in our region. In this kind of rural context, distances, low costs due to vegetable selling prices and the lack of continuous power supplies may lead to viable or inviable sensing solutions for the farmers. The proposed framework systematize and facilitates WSN designers the required complex calculations taking into account the most relevant variables regarding power consumption, avoiding full/partial/prototype implementations, and measurements of different computational load distribution potential solutions for a specific WSN. MDPI 2018-03-23 /pmc/articles/PMC5949029/ /pubmed/29570645 http://dx.doi.org/10.3390/s18040954 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
Sánchez-Álvarez, David
Linaje, Marino
Rodríguez-Pérez, Francisco-Javier
A Framework to Design the Computational Load Distribution of Wireless Sensor Networks in Power Consumption Constrained Environments
title A Framework to Design the Computational Load Distribution of Wireless Sensor Networks in Power Consumption Constrained Environments
title_full A Framework to Design the Computational Load Distribution of Wireless Sensor Networks in Power Consumption Constrained Environments
title_fullStr A Framework to Design the Computational Load Distribution of Wireless Sensor Networks in Power Consumption Constrained Environments
title_full_unstemmed A Framework to Design the Computational Load Distribution of Wireless Sensor Networks in Power Consumption Constrained Environments
title_short A Framework to Design the Computational Load Distribution of Wireless Sensor Networks in Power Consumption Constrained Environments
title_sort framework to design the computational load distribution of wireless sensor networks in power consumption constrained environments
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5949029/
https://www.ncbi.nlm.nih.gov/pubmed/29570645
http://dx.doi.org/10.3390/s18040954
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