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Dynamic Load Balancing Data Centric Storage for Wireless Sensor Networks

In this paper, a new data centric storage that is dynamically adapted to the work load changes is proposed. The proposed data centric storage distributes the load of hot spot areas to neighboring sensor nodes by using a multilevel grid technique. The proposed method is also able to use existing rout...

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Detalles Bibliográficos
Autores principales: Song, Seokil, Bok, Kyoungsoo, Kwak, Yun Sik, Goo, Bongeun, Kwak, Youngsik, Ko, Daesik
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Molecular Diversity Preservation International (MDPI) 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3230990/
https://www.ncbi.nlm.nih.gov/pubmed/22163472
http://dx.doi.org/10.3390/s101110328
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author Song, Seokil
Bok, Kyoungsoo
Kwak, Yun Sik
Goo, Bongeun
Kwak, Youngsik
Ko, Daesik
author_facet Song, Seokil
Bok, Kyoungsoo
Kwak, Yun Sik
Goo, Bongeun
Kwak, Youngsik
Ko, Daesik
author_sort Song, Seokil
collection PubMed
description In this paper, a new data centric storage that is dynamically adapted to the work load changes is proposed. The proposed data centric storage distributes the load of hot spot areas to neighboring sensor nodes by using a multilevel grid technique. The proposed method is also able to use existing routing protocols such as GPSR (Greedy Perimeter Stateless Routing) with small changes. Through simulation, the proposed method enhances the lifetime of sensor networks over one of the state-of-the-art data centric storages. We implement the proposed method based on an operating system for sensor networks, and evaluate the performance through running based on a simulation tool.
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spelling pubmed-32309902011-12-07 Dynamic Load Balancing Data Centric Storage for Wireless Sensor Networks Song, Seokil Bok, Kyoungsoo Kwak, Yun Sik Goo, Bongeun Kwak, Youngsik Ko, Daesik Sensors (Basel) Article In this paper, a new data centric storage that is dynamically adapted to the work load changes is proposed. The proposed data centric storage distributes the load of hot spot areas to neighboring sensor nodes by using a multilevel grid technique. The proposed method is also able to use existing routing protocols such as GPSR (Greedy Perimeter Stateless Routing) with small changes. Through simulation, the proposed method enhances the lifetime of sensor networks over one of the state-of-the-art data centric storages. We implement the proposed method based on an operating system for sensor networks, and evaluate the performance through running based on a simulation tool. Molecular Diversity Preservation International (MDPI) 2010-11-17 /pmc/articles/PMC3230990/ /pubmed/22163472 http://dx.doi.org/10.3390/s101110328 Text en © 2010 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/. (http://creativecommons.org/licenses/by/3.0/) )
spellingShingle Article
Song, Seokil
Bok, Kyoungsoo
Kwak, Yun Sik
Goo, Bongeun
Kwak, Youngsik
Ko, Daesik
Dynamic Load Balancing Data Centric Storage for Wireless Sensor Networks
title Dynamic Load Balancing Data Centric Storage for Wireless Sensor Networks
title_full Dynamic Load Balancing Data Centric Storage for Wireless Sensor Networks
title_fullStr Dynamic Load Balancing Data Centric Storage for Wireless Sensor Networks
title_full_unstemmed Dynamic Load Balancing Data Centric Storage for Wireless Sensor Networks
title_short Dynamic Load Balancing Data Centric Storage for Wireless Sensor Networks
title_sort dynamic load balancing data centric storage for wireless sensor networks
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3230990/
https://www.ncbi.nlm.nih.gov/pubmed/22163472
http://dx.doi.org/10.3390/s101110328
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