Detalhes bibliográficos
| Ano de defesa: |
2016 |
| Autor(a) principal: |
Conterato, Marcelo da Silva
 |
| Orientador(a): |
Ferreto, Tiago Coelho
|
| Banca de defesa: |
Não Informado pela instituição |
| Tipo de documento: |
Dissertação
|
| Tipo de acesso: |
Acesso aberto |
| Idioma: |
por |
| Instituição de defesa: |
Pontifícia Universidade Católica do Rio Grande do Sul
|
| Programa de Pós-Graduação: |
Programa de Pós-Graduação em Ciência da Computação
|
| Departamento: |
Faculdade de Informática
|
| País: |
Brasil
|
| Palavras-chave em Português: |
|
| Área do conhecimento CNPq: |
|
| Link de acesso: |
http://tede2.pucrs.br/tede2/handle/tede/6831
|
Resumo: |
Currently, Data Centers have their resources used at extremely high loads, which leads to the uncontrolled use of resources. It maintains a high energy consumption, even at times when traffic demand is low. At this time, researchers are performing several researches in energy efficiency for data center, however, most of the results were focused on two major components: servers and cooling systems. In this study, we propose strategies for data center network configuration to reduce energy consumption through the Software Defined Networking paradigm. Such strategies were combined with techniques to reduce energy consumption and evaluated compared to the power-agnostic environments. Besides, the impact of different fat-tree topology sizes and proposed strategies were simulated and compared taking into account the presented energy savings. By applying the overload factors of 1:5 and 1:20, energy-saving rate on the network reached 70.02% for a fat-tree topology size of k = 12, and 64.82% for a fat-tree topology size of k = 8, when compared to a traditional network. |
