The self-configuration of nodes using RSSI in a dense wireless sensor network

Detalhes bibliográficos
Autor(a) principal: Abdellatif,MM
Data de Publicação: 2016
Outros Autores: José Manuel Oliveira, Manuel Ricardo
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://repositorio.inesctec.pt/handle/123456789/4314
http://dx.doi.org/10.1007/s11235-015-0105-7
Resumo: Wireless sensor networks (WSNs) may be made of a large amount of small devices that are able to sense changes in the environment, and communicate these changes throughout the network. An example of a similar network is a photo voltaic (PV) power plant, where there is a sensor connected to each solar panel. The task of each sensor is to sense the output of the panel which is then sent to a central node for processing. As the network grows, it becomes impractical and even impossible to configure all these nodes manually. And so, the use of self-organization and auto-configuration algorithms becomes essential. In this paper, three algorithms are proposed that allow nodes in the network to automatically identify their closest neighbors, relative location in the network, and select which frequency channel to operate in. This is done using the value of the Received Signal Strength Indicator (RSSI) of the messages sent and received during the setup phase. The performance of these algorithms is tested by means of both simulations and testbed experiments. Results show that the error in the performance of the algorithms decreases as we increase the number of RSSI values used for decision making. Additionally, the number of nodes in the network affects the setup error. However, the value of the error is still acceptable even with a high number of nodes.
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spelling The self-configuration of nodes using RSSI in a dense wireless sensor networkWireless sensor networks (WSNs) may be made of a large amount of small devices that are able to sense changes in the environment, and communicate these changes throughout the network. An example of a similar network is a photo voltaic (PV) power plant, where there is a sensor connected to each solar panel. The task of each sensor is to sense the output of the panel which is then sent to a central node for processing. As the network grows, it becomes impractical and even impossible to configure all these nodes manually. And so, the use of self-organization and auto-configuration algorithms becomes essential. In this paper, three algorithms are proposed that allow nodes in the network to automatically identify their closest neighbors, relative location in the network, and select which frequency channel to operate in. This is done using the value of the Received Signal Strength Indicator (RSSI) of the messages sent and received during the setup phase. The performance of these algorithms is tested by means of both simulations and testbed experiments. Results show that the error in the performance of the algorithms decreases as we increase the number of RSSI values used for decision making. Additionally, the number of nodes in the network affects the setup error. However, the value of the error is still acceptable even with a high number of nodes.2017-12-19T19:33:33Z2016-01-01T00:00:00Z2016info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://repositorio.inesctec.pt/handle/123456789/4314http://dx.doi.org/10.1007/s11235-015-0105-7engAbdellatif,MMJosé Manuel OliveiraManuel Ricardoinfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-05-15T10:20:07Zoai:repositorio.inesctec.pt:123456789/4314Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T17:52:42.091292Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv The self-configuration of nodes using RSSI in a dense wireless sensor network
title The self-configuration of nodes using RSSI in a dense wireless sensor network
spellingShingle The self-configuration of nodes using RSSI in a dense wireless sensor network
Abdellatif,MM
title_short The self-configuration of nodes using RSSI in a dense wireless sensor network
title_full The self-configuration of nodes using RSSI in a dense wireless sensor network
title_fullStr The self-configuration of nodes using RSSI in a dense wireless sensor network
title_full_unstemmed The self-configuration of nodes using RSSI in a dense wireless sensor network
title_sort The self-configuration of nodes using RSSI in a dense wireless sensor network
author Abdellatif,MM
author_facet Abdellatif,MM
José Manuel Oliveira
Manuel Ricardo
author_role author
author2 José Manuel Oliveira
Manuel Ricardo
author2_role author
author
dc.contributor.author.fl_str_mv Abdellatif,MM
José Manuel Oliveira
Manuel Ricardo
description Wireless sensor networks (WSNs) may be made of a large amount of small devices that are able to sense changes in the environment, and communicate these changes throughout the network. An example of a similar network is a photo voltaic (PV) power plant, where there is a sensor connected to each solar panel. The task of each sensor is to sense the output of the panel which is then sent to a central node for processing. As the network grows, it becomes impractical and even impossible to configure all these nodes manually. And so, the use of self-organization and auto-configuration algorithms becomes essential. In this paper, three algorithms are proposed that allow nodes in the network to automatically identify their closest neighbors, relative location in the network, and select which frequency channel to operate in. This is done using the value of the Received Signal Strength Indicator (RSSI) of the messages sent and received during the setup phase. The performance of these algorithms is tested by means of both simulations and testbed experiments. Results show that the error in the performance of the algorithms decreases as we increase the number of RSSI values used for decision making. Additionally, the number of nodes in the network affects the setup error. However, the value of the error is still acceptable even with a high number of nodes.
publishDate 2016
dc.date.none.fl_str_mv 2016-01-01T00:00:00Z
2016
2017-12-19T19:33:33Z
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dc.identifier.uri.fl_str_mv http://repositorio.inesctec.pt/handle/123456789/4314
http://dx.doi.org/10.1007/s11235-015-0105-7
url http://repositorio.inesctec.pt/handle/123456789/4314
http://dx.doi.org/10.1007/s11235-015-0105-7
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