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Dynamic Task Allocation in Multi-Hop Multimedia Wireless Sensor Networks with Low Mobility

This paper presents a task allocation-oriented framework to enable efficient in-network processing and cost-effective multi-hop resource sharing for dynamic multi-hop multimedia wireless sensor networks with low node mobility, e.g., pedestrian speeds. The proposed system incorporates a fast task rea...

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Detalles Bibliográficos
Autores principales: Jin, Yichao, Vural, Serdar, Gluhak, Alexander, Moessner, Klaus
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Molecular Diversity Preservation International (MDPI) 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3859105/
https://www.ncbi.nlm.nih.gov/pubmed/24135992
http://dx.doi.org/10.3390/s131013998
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author Jin, Yichao
Vural, Serdar
Gluhak, Alexander
Moessner, Klaus
author_facet Jin, Yichao
Vural, Serdar
Gluhak, Alexander
Moessner, Klaus
author_sort Jin, Yichao
collection PubMed
description This paper presents a task allocation-oriented framework to enable efficient in-network processing and cost-effective multi-hop resource sharing for dynamic multi-hop multimedia wireless sensor networks with low node mobility, e.g., pedestrian speeds. The proposed system incorporates a fast task reallocation algorithm to quickly recover from possible network service disruptions, such as node or link failures. An evolutional self-learning mechanism based on a genetic algorithm continuously adapts the system parameters in order to meet the desired application delay requirements, while also achieving a sufficiently long network lifetime. Since the algorithm runtime incurs considerable time delay while updating task assignments, we introduce an adaptive window size to limit the delay periods and ensure an up-to-date solution based on node mobility patterns and device processing capabilities. To the best of our knowledge, this is the first study that yields multi-objective task allocation in a mobile multi-hop wireless environment under dynamic conditions. Simulations are performed in various settings, and the results show considerable performance improvement in extending network lifetime compared to heuristic mechanisms. Furthermore, the proposed framework provides noticeable reduction in the frequency of missing application deadlines.
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spelling pubmed-38591052013-12-11 Dynamic Task Allocation in Multi-Hop Multimedia Wireless Sensor Networks with Low Mobility Jin, Yichao Vural, Serdar Gluhak, Alexander Moessner, Klaus Sensors (Basel) Article This paper presents a task allocation-oriented framework to enable efficient in-network processing and cost-effective multi-hop resource sharing for dynamic multi-hop multimedia wireless sensor networks with low node mobility, e.g., pedestrian speeds. The proposed system incorporates a fast task reallocation algorithm to quickly recover from possible network service disruptions, such as node or link failures. An evolutional self-learning mechanism based on a genetic algorithm continuously adapts the system parameters in order to meet the desired application delay requirements, while also achieving a sufficiently long network lifetime. Since the algorithm runtime incurs considerable time delay while updating task assignments, we introduce an adaptive window size to limit the delay periods and ensure an up-to-date solution based on node mobility patterns and device processing capabilities. To the best of our knowledge, this is the first study that yields multi-objective task allocation in a mobile multi-hop wireless environment under dynamic conditions. Simulations are performed in various settings, and the results show considerable performance improvement in extending network lifetime compared to heuristic mechanisms. Furthermore, the proposed framework provides noticeable reduction in the frequency of missing application deadlines. Molecular Diversity Preservation International (MDPI) 2013-10-16 /pmc/articles/PMC3859105/ /pubmed/24135992 http://dx.doi.org/10.3390/s131013998 Text en © 2013 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
Jin, Yichao
Vural, Serdar
Gluhak, Alexander
Moessner, Klaus
Dynamic Task Allocation in Multi-Hop Multimedia Wireless Sensor Networks with Low Mobility
title Dynamic Task Allocation in Multi-Hop Multimedia Wireless Sensor Networks with Low Mobility
title_full Dynamic Task Allocation in Multi-Hop Multimedia Wireless Sensor Networks with Low Mobility
title_fullStr Dynamic Task Allocation in Multi-Hop Multimedia Wireless Sensor Networks with Low Mobility
title_full_unstemmed Dynamic Task Allocation in Multi-Hop Multimedia Wireless Sensor Networks with Low Mobility
title_short Dynamic Task Allocation in Multi-Hop Multimedia Wireless Sensor Networks with Low Mobility
title_sort dynamic task allocation in multi-hop multimedia wireless sensor networks with low mobility
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3859105/
https://www.ncbi.nlm.nih.gov/pubmed/24135992
http://dx.doi.org/10.3390/s131013998
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