Detalhes bibliográficos
Ano de defesa: |
2019 |
Autor(a) principal: |
Espírito Santo, Walter do |
Orientador(a): |
Ribeiro, Admilson de Ribamar Lima |
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: |
Não Informado pela instituição
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Programa de Pós-Graduação: |
Pós-Graduação em Ciência da Computação
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Departamento: |
Não Informado pela instituição
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País: |
Não Informado pela instituição
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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: |
https://ri.ufs.br/jspui/handle/riufs/18340
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Resumo: |
The Internet of Things (IoT) is an emerging technology paradigm in which ubiquitous sensors monitor, physical infrastructure, environments and people in real time to make decisions that improve systems efficiency and reliability while adding comfort and quality of life to society. IoT data storage and processing are commonly performed on cloud computing infrastructures, but issues such as computational resource constraints, high latency, and different quality of service (QoS) requirements related to IoT devices that eventually move cloud technologies around. towards fog computing, and the adoption of light virtualization solutions such as container-based technologies to address the diverse needs of different domains. The present study aims to propose and implement a micro Platform as a Service (micro-PaaS) architecture in fog computing, in a single board computer (SBC) cluster. The proposed architecture encompasses application orchestration using containers, applied to the Internet of Things and meeting QoS criteria such as high availability, scalability, load balancing and latency. Based on the proposed model, the micro-PaaS Fog was implemented with container virtualization technology using orchestration services in a cluster of Raspberry Pi devices for intelligent monitoring of water and energy consumption at Sergipe Campus Lagarto Federal Institute focal points. . The results showed that it is possible to implement a performance micro-PaaS Fog at a total cost of ownership (TCO) equivalent to 23% of a public platform as a service (PaaS), 26m average mote-fog latency and average recovery time. 1.33 second failures taking into account a confidence interval (CI) of 95%. This research also contributed to a systematic mapping to identify key features and requirements for efficient orchestration in fog computing environments. Through a comparative study, the following characteristics were identified as being the most commonly addressed in this area: heterogeneity, QoS management, scalability, mobility, federation, and interoperability. |