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Network Modeling and Energy-Efficiency Optimization for Advanced Machine-to-Machine Sensor Networks

Wireless machine-to-machine sensor networks with multiple radio interfaces are expected to have several advantages, including high spatial scalability, low event detection latency, and low energy consumption. Here, we propose a network model design method involving network approximation and an optim...

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Detalles Bibliográficos
Autores principales: Jung, Sungmo, Kim, Jong Hyun, Kim, Seoksoo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Molecular Diversity Preservation International (MDPI) 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3522943/
https://www.ncbi.nlm.nih.gov/pubmed/23202190
http://dx.doi.org/10.3390/s121114851
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author Jung, Sungmo
Kim, Jong Hyun
Kim, Seoksoo
author_facet Jung, Sungmo
Kim, Jong Hyun
Kim, Seoksoo
author_sort Jung, Sungmo
collection PubMed
description Wireless machine-to-machine sensor networks with multiple radio interfaces are expected to have several advantages, including high spatial scalability, low event detection latency, and low energy consumption. Here, we propose a network model design method involving network approximation and an optimized multi-tiered clustering algorithm that maximizes node lifespan by minimizing energy consumption in a non-uniformly distributed network. Simulation results show that the cluster scales and network parameters determined with the proposed method facilitate a more efficient performance compared to existing methods.
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spelling pubmed-35229432013-01-09 Network Modeling and Energy-Efficiency Optimization for Advanced Machine-to-Machine Sensor Networks Jung, Sungmo Kim, Jong Hyun Kim, Seoksoo Sensors (Basel) Article Wireless machine-to-machine sensor networks with multiple radio interfaces are expected to have several advantages, including high spatial scalability, low event detection latency, and low energy consumption. Here, we propose a network model design method involving network approximation and an optimized multi-tiered clustering algorithm that maximizes node lifespan by minimizing energy consumption in a non-uniformly distributed network. Simulation results show that the cluster scales and network parameters determined with the proposed method facilitate a more efficient performance compared to existing methods. Molecular Diversity Preservation International (MDPI) 2012-11-05 /pmc/articles/PMC3522943/ /pubmed/23202190 http://dx.doi.org/10.3390/s121114851 Text en © 2012 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 license (http://creativecommons.org/licenses/by/3.0/).
spellingShingle Article
Jung, Sungmo
Kim, Jong Hyun
Kim, Seoksoo
Network Modeling and Energy-Efficiency Optimization for Advanced Machine-to-Machine Sensor Networks
title Network Modeling and Energy-Efficiency Optimization for Advanced Machine-to-Machine Sensor Networks
title_full Network Modeling and Energy-Efficiency Optimization for Advanced Machine-to-Machine Sensor Networks
title_fullStr Network Modeling and Energy-Efficiency Optimization for Advanced Machine-to-Machine Sensor Networks
title_full_unstemmed Network Modeling and Energy-Efficiency Optimization for Advanced Machine-to-Machine Sensor Networks
title_short Network Modeling and Energy-Efficiency Optimization for Advanced Machine-to-Machine Sensor Networks
title_sort network modeling and energy-efficiency optimization for advanced machine-to-machine sensor networks
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3522943/
https://www.ncbi.nlm.nih.gov/pubmed/23202190
http://dx.doi.org/10.3390/s121114851
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