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Service-Aware Clustering: An Energy-Efficient Model for the Internet-of-Things
Current generation wireless sensor routing algorithms and protocols have been designed based on a myopic routing approach, where the motes are assumed to have the same sensing and communication capabilities. Myopic routing is not a natural fit for the IoT, as it may lead to energy imbalance and subs...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4732042/ https://www.ncbi.nlm.nih.gov/pubmed/26703619 http://dx.doi.org/10.3390/s16010009 |
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author | Bagula, Antoine Abidoye, Ademola Philip Zodi, Guy-Alain Lusilao |
author_facet | Bagula, Antoine Abidoye, Ademola Philip Zodi, Guy-Alain Lusilao |
author_sort | Bagula, Antoine |
collection | PubMed |
description | Current generation wireless sensor routing algorithms and protocols have been designed based on a myopic routing approach, where the motes are assumed to have the same sensing and communication capabilities. Myopic routing is not a natural fit for the IoT, as it may lead to energy imbalance and subsequent short-lived sensor networks, routing the sensor readings over the most service-intensive sensor nodes, while leaving the least active nodes idle. This paper revisits the issue of energy efficiency in sensor networks to propose a clustering model where sensor devices’ service delivery is mapped into an energy awareness model, used to design a clustering algorithm that finds service-aware clustering (SAC) configurations in IoT settings. The performance evaluation reveals the relative energy efficiency of the proposed SAC algorithm compared to related routing algorithms in terms of energy consumption, the sensor nodes’ life span and its traffic engineering efficiency in terms of throughput and delay. These include the well-known low energy adaptive clustering hierarchy (LEACH) and LEACH-centralized (LEACH-C) algorithms, as well as the most recent algorithms, such as DECSA and MOCRN. |
format | Online Article Text |
id | pubmed-4732042 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-47320422016-02-12 Service-Aware Clustering: An Energy-Efficient Model for the Internet-of-Things Bagula, Antoine Abidoye, Ademola Philip Zodi, Guy-Alain Lusilao Sensors (Basel) Article Current generation wireless sensor routing algorithms and protocols have been designed based on a myopic routing approach, where the motes are assumed to have the same sensing and communication capabilities. Myopic routing is not a natural fit for the IoT, as it may lead to energy imbalance and subsequent short-lived sensor networks, routing the sensor readings over the most service-intensive sensor nodes, while leaving the least active nodes idle. This paper revisits the issue of energy efficiency in sensor networks to propose a clustering model where sensor devices’ service delivery is mapped into an energy awareness model, used to design a clustering algorithm that finds service-aware clustering (SAC) configurations in IoT settings. The performance evaluation reveals the relative energy efficiency of the proposed SAC algorithm compared to related routing algorithms in terms of energy consumption, the sensor nodes’ life span and its traffic engineering efficiency in terms of throughput and delay. These include the well-known low energy adaptive clustering hierarchy (LEACH) and LEACH-centralized (LEACH-C) algorithms, as well as the most recent algorithms, such as DECSA and MOCRN. MDPI 2015-12-23 /pmc/articles/PMC4732042/ /pubmed/26703619 http://dx.doi.org/10.3390/s16010009 Text en © 2015 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons by Attribution (CC-BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Bagula, Antoine Abidoye, Ademola Philip Zodi, Guy-Alain Lusilao Service-Aware Clustering: An Energy-Efficient Model for the Internet-of-Things |
title | Service-Aware Clustering: An Energy-Efficient Model for the Internet-of-Things |
title_full | Service-Aware Clustering: An Energy-Efficient Model for the Internet-of-Things |
title_fullStr | Service-Aware Clustering: An Energy-Efficient Model for the Internet-of-Things |
title_full_unstemmed | Service-Aware Clustering: An Energy-Efficient Model for the Internet-of-Things |
title_short | Service-Aware Clustering: An Energy-Efficient Model for the Internet-of-Things |
title_sort | service-aware clustering: an energy-efficient model for the internet-of-things |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4732042/ https://www.ncbi.nlm.nih.gov/pubmed/26703619 http://dx.doi.org/10.3390/s16010009 |
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