Uma abordagem de processamento de consultas para plataformas de middleware distribuído e particionado no contexto de cidades inteligentes

Detalhes bibliográficos
Ano de defesa: 2019
Autor(a) principal: Lopes, Júlio Zinga Suzuki
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: Universidade Federal da Paraíba
Brasil
Informática
Programa de Pós-Graduação em Informática
UFPB
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://repositorio.ufpb.br/jspui/handle/123456789/19444
Resumo: Nowadays, more than half of the world's population lives in cities. It is expected to reach five billion people by 2030. This fast population growth in major centers will present biggest challenges, such as air pollution, urban mobility, health problems, energy and waste management. Solutions to these challenges require the integration of various Information and Communication Technologies (ICTs) in different domains. Cities that exploit these solutions, using ICTs to help solve their problems, have been called Smart Cities. However, the first solutions created had some limitations, as they were generally based on independent systems, with different technologies and without the concern with interoperability and scalability. In this context, middleware platforms have been used as infrastructure to assist the development of Smart City applications, systems and services. Among the main challenges of these platforms, data integration is very representative, as it allows users to provide consolidated information from different providers with transparency of location and representation format. In this sense, this paper proposes a query processing approach for distributed and partitioned middleware platforms, whose information is stored in different data providers and geographically distributed. A case study with significant volume of semi-public transit data was developed to validate and evaluate the proposed approach. In the performed case study, five distributed scenarios involving up to 10 platform servers, with 10,000 instances of context entities were used to evalute this proposal. In each scenario, the throughput in query processing was evaluated. Thus, compared to Orion Context Broker, a data provider widely used in European Smart Cities projects, the proposed approach was able to achieve a throughput exceeding 1.600%.