Detalhes bibliográficos
| Ano de defesa: |
2022 |
| Autor(a) principal: |
Cordeiro, Bruna Michelly de Oliveira Silva
 |
| Orientador(a): |
Costa, Fábio Moreira
|
| Banca de defesa: |
Costa, Fábio Moreira,
Sene Junior, Iwens Gervasio,
Rodrigues Filho, Roberto,
Oliveira Junior, Antonio Carlos de,
Ueyama, Jó |
| 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: |
Programa de Pós-graduação em Ciência da Computação (INF)
|
| Departamento: |
Instituto de Informática - INF (RG)
|
| País: |
Brasil
|
| 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/tede/12211
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Resumo: |
Smart Cities have an operating environment with high volatility, where frequent changes occur, forcing systems to deal with new situations. Specifically in IoT networks, which make up the infrastructure of devices in the city, this volatility demands the ability to quickly and correctly change the network behavior at runtime. In light of this, the management of IoT networks for smart cities has a high level of complexity. In order to facilitate the (re)programming of network behavior, the concept of Software Defined Networks (SDN) for IoT is gaining popularity and has been applied to control this type of network. A concept present in the literature that has the potential to abstract some of this complexity refers to Intent-Driven Networks (IDN). The application of this concept allows the programming of the network by means of intentions, built using a high-level declarative language. This work explores the combination of IDN and SDN to abstract and facilitate the programming and adaptation of the IoT network behavior, according to intentions defined by applications at runtime. In this work, SDN mechanisms are used to perform the deployment of network functions that define and/or change the behavior of the network nodes, while IDN is used to abstract the programming of the network behavior, as well as allow fine-grained adjustments of that behavior. The behavior to be implemented in the network is chosen at runtime, based on intentions coming from the application. This choice is made by a decision making algorithm, which by means of a metric, is able to determine the best behavior in function of the current state of the network. Simulation-based experiments were conducted to validate this intent processing in different usage scenarios. |
