Detalhes bibliográficos
| Ano de defesa: |
2010 |
| Autor(a) principal: |
OLIVEIRA, Thiago Borges de
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| Orientador(a): |
RODRIGUES, Vagner José do Sacramento
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| Banca de defesa: |
Não Informado pela instituição |
| Tipo de documento: |
Dissertação
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| Tipo de acesso: |
Acesso aberto |
| Idioma: |
por |
| Instituição de defesa: |
Universidade Federal de Goiás
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| Programa de Pós-Graduação: |
Mestrado em Ciência da Computação
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| Departamento: |
Ciências Exatas e da Terra - Ciências da Computação
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| País: |
BR
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| Palavras-chave em Português: |
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| Palavras-chave em Inglês: |
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| Área do conhecimento CNPq: |
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| Link de acesso: |
http://repositorio.bc.ufg.br/tede/handle/tde/506
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Resumo: |
The demand for spatial data processing systems that support the creation of massive applications has steadily grown in the increasingly ubiquitous computing world. These demands aims to explore the large amount of existing data to assist people s daily lives and provide new tools for business and government. Most of the current solutions to process spatial data do not meet the scalability needed, and thus new solutions that efficiently use distributed computing resources are needed. This work presents a distributed and scalable system called DSI-RTree, which implements a distributed index to process spatial data in a cluster of computers. We also have done a review of details related to the construction of the distributed spatial index, by addressing issues such as the size of data partitions, how that partitions are distributed and the impact of these definitions in the message flow on the cluster. An equation to calculate the size of the partitions based on the size of data sets is proposed, to ensure efficiently query processing on the proposed architecture. We have done some experiments running window queries in spatial data sets of 33,000 and 158,000 polygons and the results showed a scalability greater than linear. |
