Detalhes bibliográficos
Ano de defesa: |
2012 |
Autor(a) principal: |
Siqueira Junior, Manoel Mariano |
Orientador(a): |
Não Informado pela instituição |
Banca de defesa: |
Não Informado pela instituição |
Tipo de documento: |
Dissertação
|
Tipo de acesso: |
Acesso aberto |
Idioma: |
por |
Instituição de defesa: |
Não Informado pela instituição
|
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: |
http://www.repositorio.ufc.br/handle/riufc/18497
|
Resumo: |
Cloud computing is a recent trend of technology aimed at providing services for Information Technology (IT) and demand-based payment in use. One of the main services provided by a computing platform cloud is the service data management, or simply data service. This service accepts responsibility for the installation, configuration and maintenance of database systems, as well as for efficient access to stored data. This work presents a framework, called GeDaNIC, for managing database systems cloud data. The proposed framework aims to provide software infrastructure required for the provision of data services in computing environments cloud. Accordingly, the search system designed to solve some problems still in the context of open systems database in the cloud, such as dispatch, scheduling appointments and resource provisioning. The approach extends the designed Previous work by adding important features such as: support to unforeseen workloads and use of information about the interactions between queries. The supporting seasonal workloads is related to one of the main properties of computing Cloud: rapid elasticity. Already interactions between queries can provide impacts significant performance of database systems. For this reason, the GeDaNIC uses information about these interactions in order to reduce the execution time of workloads submitted to the data service and thereby increase the profit of provider of this service. For this, three new approaches to model and measure the interactions between instances and types of queries are proposed. In order to demonstrate the efficiency of the proposed framework for experimental evaluation using the TPC-H on PostgreSQL was performed. The results show that the designed solution has the potential to increase the profit of the service provider cloud data. |