| Texto completo | |
| Autor(es): |
da Silva, Rodrigo A. C.
;
da Fonseca, Nelson L. S.
;
IEEE
Número total de Autores: 3
|
| Tipo de documento: | Artigo Científico |
| Fonte: | 2018 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS (ICC); v. N/A, p. 6-pg., 2018-01-01. |
| Resumo | |
Fog computing brings the cloud close to the users, reducing latency and allowing the deployment of new delay-sensitive applications. Fogs and clouds can work cooperatively to improve service delivery to the end users. An essential aspect of a fog-cloud system is the decision-making process on where to allocate resources to run the tasks of an application. This paper introduces a novel mechanism named Gaussian Process Regression for Fog-Cloud Allocation (GPRFCA) for resource allocation in infrastructure composed of cooperative fogs and clouds. The GPRFCA mechanism employs a Gaussian Process Regression to predict future demands in order to avoid blocking of requests, especially delay-sensitive ones. Results show that the GPRFCA mechanism reduces energy consumption, blocking as well as latency. (AU) | |
| Processo FAPESP: | 15/24494-8 - Comunicação e processamento de big data em nuvens e névoas computacionais |
| Beneficiário: | Nelson Luis Saldanha da Fonseca |
| Modalidade de apoio: | Auxílio à Pesquisa - Temático |