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Model-Based Design of Tree WSNs for Decentralized Detection †

The classical decentralized detection problem of finding the optimal decision rules at the sensor and fusion center, as well as variants that introduce physical channel impairments have been studied extensively in the literature. The deployment of WSNs in decentralized detection applications brings...

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Detalles Bibliográficos
Autores principales: Tantawy, Ashraf, Koutsoukos, Xenofon, Biswas, Gautam
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4570439/
https://www.ncbi.nlm.nih.gov/pubmed/26307989
http://dx.doi.org/10.3390/s150820608
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author Tantawy, Ashraf
Koutsoukos, Xenofon
Biswas, Gautam
author_facet Tantawy, Ashraf
Koutsoukos, Xenofon
Biswas, Gautam
author_sort Tantawy, Ashraf
collection PubMed
description The classical decentralized detection problem of finding the optimal decision rules at the sensor and fusion center, as well as variants that introduce physical channel impairments have been studied extensively in the literature. The deployment of WSNs in decentralized detection applications brings new challenges to the field. Protocols for different communication layers have to be co-designed to optimize the detection performance. In this paper, we consider the communication network design problem for a tree WSN. We pursue a system-level approach where a complete model for the system is developed that captures the interactions between different layers, as well as different sensor quality measures. For network optimization, we propose a hierarchical optimization algorithm that lends itself to the tree structure, requiring only local network information. The proposed design approach shows superior performance over several contentionless and contention-based network design approaches.
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spelling pubmed-45704392015-09-17 Model-Based Design of Tree WSNs for Decentralized Detection † Tantawy, Ashraf Koutsoukos, Xenofon Biswas, Gautam Sensors (Basel) Article The classical decentralized detection problem of finding the optimal decision rules at the sensor and fusion center, as well as variants that introduce physical channel impairments have been studied extensively in the literature. The deployment of WSNs in decentralized detection applications brings new challenges to the field. Protocols for different communication layers have to be co-designed to optimize the detection performance. In this paper, we consider the communication network design problem for a tree WSN. We pursue a system-level approach where a complete model for the system is developed that captures the interactions between different layers, as well as different sensor quality measures. For network optimization, we propose a hierarchical optimization algorithm that lends itself to the tree structure, requiring only local network information. The proposed design approach shows superior performance over several contentionless and contention-based network design approaches. MDPI 2015-08-20 /pmc/articles/PMC4570439/ /pubmed/26307989 http://dx.doi.org/10.3390/s150820608 Text en © 2015 by the authors; licensee MDPI, Basel, Switzerland. https://creativecommons.org/licenses/by/4.0/This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ).
spellingShingle Article
Tantawy, Ashraf
Koutsoukos, Xenofon
Biswas, Gautam
Model-Based Design of Tree WSNs for Decentralized Detection †
title Model-Based Design of Tree WSNs for Decentralized Detection †
title_full Model-Based Design of Tree WSNs for Decentralized Detection †
title_fullStr Model-Based Design of Tree WSNs for Decentralized Detection †
title_full_unstemmed Model-Based Design of Tree WSNs for Decentralized Detection †
title_short Model-Based Design of Tree WSNs for Decentralized Detection †
title_sort model-based design of tree wsns for decentralized detection †
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4570439/
https://www.ncbi.nlm.nih.gov/pubmed/26307989
http://dx.doi.org/10.3390/s150820608
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