Localização de sensores considerando custo mínimo
| Ano de defesa: | 2013 |
|---|---|
| Autor(a) principal: | |
| Orientador(a): | |
| Banca de defesa: | |
| Tipo de documento: | Dissertação |
| Tipo de acesso: | Acesso aberto |
| Idioma: | por |
| Instituição de defesa: |
Universidade Federal de Minas Gerais
|
| Programa de Pós-Graduação: |
Não Informado pela instituição
|
| Departamento: |
Não Informado pela instituição
|
| País: |
Não Informado pela instituição
|
| Palavras-chave em Português: | |
| Link de acesso: | https://hdl.handle.net/1843/ESBF-97CMA7 |
Resumo: | Localization is one of the key issues in Wireless Sensor Networks. Its use is undoubtedlyimportant in many different applications. However, its often required to minimize thelocalization cost in a network. This can be done by setting some nodes as anchors,which are used as reference to other nodes. Current literature solutions focus on findingas many nodes as possible given a static set of anchor nodes, providing each one of thesenodes resources such as a GPS to determine its location. On the other hand, this maybe unfeasible for many sensor networks due to the high cost and/or implementationcomplexity. The optimization problem presented in this work consists of finding theminimum set of anchor nodes needed to locate all nodes in the network. Anotherapproach is to find the shortest path between the anchors. This way a robot can beused to visit and set the exact position of the nodes that work as anchors, that is, it isonly necessary to minimize the path, since the localization cost is the robot fuel. Hereit is presented a model for the problem using Genetic Algorithms in order to createthis problem a better solution. Several tests were performed to show the effectivenessof the strategy based on the number of anchors required to locate the entire network.The results have shown that the genetic algorithm reached, on average, a 50%-bettersolution than the greedy algorithm, having a feasible runtime. |
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Localização de sensores considerando custo mínimoComputaçãoAlgoritmos genéticosRedes de sensores sem fioLocalizaçãoAlgoritmo genéticoRedes de sensores sem fioLocalization is one of the key issues in Wireless Sensor Networks. Its use is undoubtedlyimportant in many different applications. However, its often required to minimize thelocalization cost in a network. This can be done by setting some nodes as anchors,which are used as reference to other nodes. Current literature solutions focus on findingas many nodes as possible given a static set of anchor nodes, providing each one of thesenodes resources such as a GPS to determine its location. On the other hand, this maybe unfeasible for many sensor networks due to the high cost and/or implementationcomplexity. The optimization problem presented in this work consists of finding theminimum set of anchor nodes needed to locate all nodes in the network. Anotherapproach is to find the shortest path between the anchors. This way a robot can beused to visit and set the exact position of the nodes that work as anchors, that is, it isonly necessary to minimize the path, since the localization cost is the robot fuel. Hereit is presented a model for the problem using Genetic Algorithms in order to createthis problem a better solution. Several tests were performed to show the effectivenessof the strategy based on the number of anchors required to locate the entire network.The results have shown that the genetic algorithm reached, on average, a 50%-bettersolution than the greedy algorithm, having a feasible runtime.Universidade Federal de Minas Gerais2019-08-09T19:26:59Z2025-09-08T23:20:37Z2019-08-09T19:26:59Z2013-03-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttps://hdl.handle.net/1843/ESBF-97CMA7Angelo Ferreira Assisinfo:eu-repo/semantics/openAccessporreponame:Repositório Institucional da UFMGinstname:Universidade Federal de Minas Gerais (UFMG)instacron:UFMG2025-09-08T23:20:37Zoai:repositorio.ufmg.br:1843/ESBF-97CMA7Repositório InstitucionalPUBhttps://repositorio.ufmg.br/oairepositorio@ufmg.bropendoar:2025-09-08T23:20:37Repositório Institucional da UFMG - Universidade Federal de Minas Gerais (UFMG)false |
| dc.title.none.fl_str_mv |
Localização de sensores considerando custo mínimo |
| title |
Localização de sensores considerando custo mínimo |
| spellingShingle |
Localização de sensores considerando custo mínimo Angelo Ferreira Assis Computação Algoritmos genéticos Redes de sensores sem fio Localização Algoritmo genético Redes de sensores sem fio |
| title_short |
Localização de sensores considerando custo mínimo |
| title_full |
Localização de sensores considerando custo mínimo |
| title_fullStr |
Localização de sensores considerando custo mínimo |
| title_full_unstemmed |
Localização de sensores considerando custo mínimo |
| title_sort |
Localização de sensores considerando custo mínimo |
| author |
Angelo Ferreira Assis |
| author_facet |
Angelo Ferreira Assis |
| author_role |
author |
| dc.contributor.author.fl_str_mv |
Angelo Ferreira Assis |
| dc.subject.por.fl_str_mv |
Computação Algoritmos genéticos Redes de sensores sem fio Localização Algoritmo genético Redes de sensores sem fio |
| topic |
Computação Algoritmos genéticos Redes de sensores sem fio Localização Algoritmo genético Redes de sensores sem fio |
| description |
Localization is one of the key issues in Wireless Sensor Networks. Its use is undoubtedlyimportant in many different applications. However, its often required to minimize thelocalization cost in a network. This can be done by setting some nodes as anchors,which are used as reference to other nodes. Current literature solutions focus on findingas many nodes as possible given a static set of anchor nodes, providing each one of thesenodes resources such as a GPS to determine its location. On the other hand, this maybe unfeasible for many sensor networks due to the high cost and/or implementationcomplexity. The optimization problem presented in this work consists of finding theminimum set of anchor nodes needed to locate all nodes in the network. Anotherapproach is to find the shortest path between the anchors. This way a robot can beused to visit and set the exact position of the nodes that work as anchors, that is, it isonly necessary to minimize the path, since the localization cost is the robot fuel. Hereit is presented a model for the problem using Genetic Algorithms in order to createthis problem a better solution. Several tests were performed to show the effectivenessof the strategy based on the number of anchors required to locate the entire network.The results have shown that the genetic algorithm reached, on average, a 50%-bettersolution than the greedy algorithm, having a feasible runtime. |
| publishDate |
2013 |
| dc.date.none.fl_str_mv |
2013-03-01 2019-08-09T19:26:59Z 2019-08-09T19:26:59Z 2025-09-08T23:20:37Z |
| dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
| dc.type.driver.fl_str_mv |
info:eu-repo/semantics/masterThesis |
| format |
masterThesis |
| status_str |
publishedVersion |
| dc.identifier.uri.fl_str_mv |
https://hdl.handle.net/1843/ESBF-97CMA7 |
| url |
https://hdl.handle.net/1843/ESBF-97CMA7 |
| dc.language.iso.fl_str_mv |
por |
| language |
por |
| dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
| eu_rights_str_mv |
openAccess |
| dc.format.none.fl_str_mv |
application/pdf |
| dc.publisher.none.fl_str_mv |
Universidade Federal de Minas Gerais |
| publisher.none.fl_str_mv |
Universidade Federal de Minas Gerais |
| dc.source.none.fl_str_mv |
reponame:Repositório Institucional da UFMG instname:Universidade Federal de Minas Gerais (UFMG) instacron:UFMG |
| instname_str |
Universidade Federal de Minas Gerais (UFMG) |
| instacron_str |
UFMG |
| institution |
UFMG |
| reponame_str |
Repositório Institucional da UFMG |
| collection |
Repositório Institucional da UFMG |
| repository.name.fl_str_mv |
Repositório Institucional da UFMG - Universidade Federal de Minas Gerais (UFMG) |
| repository.mail.fl_str_mv |
repositorio@ufmg.br |
| _version_ |
1856413989620154368 |