Máquina de interferência autonônica distribuída para RSSF
| Ano de defesa: | 2010 |
|---|---|
| Autor(a) principal: | |
| Orientador(a): | |
| Banca de defesa: | |
| Tipo de documento: | Dissertação |
| Tipo de acesso: | Acesso aberto |
| Idioma: | por |
| Instituição de defesa: |
Não Informado pela instituição
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| Programa de Pós-Graduação: |
Não Informado pela instituição
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| Departamento: |
Não Informado pela instituição
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| País: |
Não Informado pela instituição
|
| Palavras-chave em Português: | |
| Link de acesso: | http://www.repositorio.ufc.br/handle/riufc/66678 |
Resumo: | Wireless sensor networks are examples of resource constrained networks (RCNs) in which processing resources, storage and energy are limited. This type of network can provide context information to Ambient Intelligence systems, which tend to overload as it increases the amount of sensor nodes in WSN and/or the degree of heterogeneity of its data types captured. This paper proposes an autonomic distributed inference machine (MIAD) that uses fuzzy logic to increase the level of semantic information in the context of WSN, and self-configures sensing intervals, dissemination of sensor nodes and redundancy message context of the monitored area. Experimental tests carried out with temperature sensors and relative humidity show that MIAD embedded in sensor nodes provides an increase of 21.8% in dispatching context information relevant to fire risk and reduces the power consumption of WSN in 18.4%. MIAD has shown better results when compared to both the producer of a distributed application framework for WSN as well as an autonomic motor based on crisp rules responsible for self-configuration of WSN. |
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Campos, Nídia Glória da SilvaGomes, Danielo GonçalvesSouza, José Neuman de2022-06-24T17:49:12Z2022-06-24T17:49:12Z2010CAMPOS, N.G.S. Máquina de interferência autonônica distribuída para RSSF. 2010. 64 F. Dissertação (Mestrado) - Universidade Federal do Ceará, Fortaleza, 2010.http://www.repositorio.ufc.br/handle/riufc/66678Wireless sensor networks are examples of resource constrained networks (RCNs) in which processing resources, storage and energy are limited. This type of network can provide context information to Ambient Intelligence systems, which tend to overload as it increases the amount of sensor nodes in WSN and/or the degree of heterogeneity of its data types captured. This paper proposes an autonomic distributed inference machine (MIAD) that uses fuzzy logic to increase the level of semantic information in the context of WSN, and self-configures sensing intervals, dissemination of sensor nodes and redundancy message context of the monitored area. Experimental tests carried out with temperature sensors and relative humidity show that MIAD embedded in sensor nodes provides an increase of 21.8% in dispatching context information relevant to fire risk and reduces the power consumption of WSN in 18.4%. MIAD has shown better results when compared to both the producer of a distributed application framework for WSN as well as an autonomic motor based on crisp rules responsible for self-configuration of WSN.Redes de Sensores Sem Fio (RSSF) são exemplos de Resource-Constrained Networks (RCNs) nas quais recursos de processamento, armazenamento e energia são limitados. Esse tipo de rede pode fornecer informações de contexto a sistemas de inteligência de ambiente, os quais tendem à sobrecarga conforme aumenta-se a quantidade de nós sensores da RSSF e/ou o grau de heterogeneidade dos seus tipos de dados capturados. Este trabalho propõe uma máquina de inferência autômica distribuída (MIAD) que usa lógica fuzzy para aumentar o nível semântico de informações de contexto da RSSF, além de autoconfigurar intervalos de sensoriamento, disseminação dos nós sensores e a redundância de mensagens de contexto da área monitorada. Testes experimentais realizados com sensores de temperatura e umidade relativa mostram que a MIAD embarcada nos nós sensores propicia aumento de 21,8% no envio de informações de contexto relevantes sobre risco de fogo, bem como diminui o consumo de energia da RSSF em 18,4%. A MIAD apresentou melhores resultados quando comparada tanto a uma aplicação distribuída produtora de contexto para RSSF quanto a um motor autonômico baseado em regras rígidas (crisp rules) responsável pela autoconfiguração da RSSF.TeleinformáticaLógica difusaSinais e sistemasMáquina de interferência autonônica distribuída para RSSFinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisporreponame:Repositório Institucional da Universidade Federal do Ceará (UFC)instname:Universidade Federal do Ceará (UFC)instacron:UFCinfo:eu-repo/semantics/openAccessLICENSElicense.txtlicense.txttext/plain; charset=utf-82152http://repositorio.ufc.br/bitstream/riufc/66678/2/license.txtfb3ad2d23d9790966439580114baefafMD52ORIGINAL2010_dis_ngscampos.pdf2010_dis_ngscampos.pdfapplication/pdf1663842http://repositorio.ufc.br/bitstream/riufc/66678/1/2010_dis_ngscampos.pdfbf51e3ad2260b2e24e0cc18ee67973ffMD51riufc/666782022-06-24 14:49:12.386oai:repositorio.ufc.br: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Repositório InstitucionalPUBhttp://www.repositorio.ufc.br/ri-oai/requestbu@ufc.br || repositorio@ufc.bropendoar:2022-06-24T17:49:12Repositório Institucional da Universidade Federal do Ceará (UFC) - Universidade Federal do Ceará (UFC)false |
| dc.title.pt_BR.fl_str_mv |
Máquina de interferência autonônica distribuída para RSSF |
| title |
Máquina de interferência autonônica distribuída para RSSF |
| spellingShingle |
Máquina de interferência autonônica distribuída para RSSF Campos, Nídia Glória da Silva Teleinformática Lógica difusa Sinais e sistemas |
| title_short |
Máquina de interferência autonônica distribuída para RSSF |
| title_full |
Máquina de interferência autonônica distribuída para RSSF |
| title_fullStr |
Máquina de interferência autonônica distribuída para RSSF |
| title_full_unstemmed |
Máquina de interferência autonônica distribuída para RSSF |
| title_sort |
Máquina de interferência autonônica distribuída para RSSF |
| author |
Campos, Nídia Glória da Silva |
| author_facet |
Campos, Nídia Glória da Silva |
| author_role |
author |
| dc.contributor.co-advisor.none.fl_str_mv |
Gomes, Danielo Gonçalves |
| dc.contributor.author.fl_str_mv |
Campos, Nídia Glória da Silva |
| dc.contributor.advisor1.fl_str_mv |
Souza, José Neuman de |
| contributor_str_mv |
Souza, José Neuman de |
| dc.subject.por.fl_str_mv |
Teleinformática Lógica difusa Sinais e sistemas |
| topic |
Teleinformática Lógica difusa Sinais e sistemas |
| description |
Wireless sensor networks are examples of resource constrained networks (RCNs) in which processing resources, storage and energy are limited. This type of network can provide context information to Ambient Intelligence systems, which tend to overload as it increases the amount of sensor nodes in WSN and/or the degree of heterogeneity of its data types captured. This paper proposes an autonomic distributed inference machine (MIAD) that uses fuzzy logic to increase the level of semantic information in the context of WSN, and self-configures sensing intervals, dissemination of sensor nodes and redundancy message context of the monitored area. Experimental tests carried out with temperature sensors and relative humidity show that MIAD embedded in sensor nodes provides an increase of 21.8% in dispatching context information relevant to fire risk and reduces the power consumption of WSN in 18.4%. MIAD has shown better results when compared to both the producer of a distributed application framework for WSN as well as an autonomic motor based on crisp rules responsible for self-configuration of WSN. |
| publishDate |
2010 |
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2010 |
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2022-06-24T17:49:12Z |
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2022-06-24T17:49:12Z |
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info:eu-repo/semantics/publishedVersion |
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info:eu-repo/semantics/masterThesis |
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masterThesis |
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publishedVersion |
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CAMPOS, N.G.S. Máquina de interferência autonônica distribuída para RSSF. 2010. 64 F. Dissertação (Mestrado) - Universidade Federal do Ceará, Fortaleza, 2010. |
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http://www.repositorio.ufc.br/handle/riufc/66678 |
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CAMPOS, N.G.S. Máquina de interferência autonônica distribuída para RSSF. 2010. 64 F. Dissertação (Mestrado) - Universidade Federal do Ceará, Fortaleza, 2010. |
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