| Full text | |
| Author(s): |
da Silva, Rodrigo A. C.
;
da Fonseca, Nelson L. S.
;
IEEE
Total Authors: 3
|
| Document type: | Journal article |
| Source: | 2018 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS (ICC); v. N/A, p. 6-pg., 2018-01-01. |
| Abstract | |
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) | |
| FAPESP's process: | 15/24494-8 - Communications and processing of big data in cloud and fog computing |
| Grantee: | Nelson Luis Saldanha da Fonseca |
| Support Opportunities: | Research Projects - Thematic Grants |