| Full text | |
| Author(s): |
Da Costa, Joahannes B. D.
;
de Souza, Allan M.
;
Rosario, Denis
;
Sommer, Christoph
;
Villas, Leandro A.
;
IEEE
Total Authors: 6
|
| Document type: | Journal article |
| Source: | 2022 IEEE 96TH VEHICULAR TECHNOLOGY CONFERENCE (VTC2022-FALL); v. N/A, p. 6-pg., 2022-01-01. |
| Abstract | |
Vehicular Edge Computing is a promising paradigm that provides cloud computing services closer to vehicular users. Vehicles and communication infrastructure can cooperatively provide vehicular services with low latency constraints through vehicular cloud formation and using these computational resources via task scheduling. An efficient task scheduler must decide which cloud will run the tasks, considering vehicular mobility and task requirements. This is important to minimize processing time and, consequently, monetary cost. However, the literature solutions do not consider these contextual aspects together, degrading the overall system efficiency. This work presents EFESTO, a task scheduling mechanism that considers contextual aspects in its decision process. The results show that, compared to state-of-the-art solutions, EFESTO can schedule more tasks while minimizing monetary cost and system latency. (AU) | |
| FAPESP's process: | 21/13780-0 - Fault-tolerant control for vehicular edge computing |
| Grantee: | Joahannes Bruno Dias da Costa |
| Support Opportunities: | Scholarships abroad - Research Internship - Doctorate |
| FAPESP's process: | 18/16703-4 - Vehicular cloud computing for information management in intelligent transportation systems |
| Grantee: | Joahannes Bruno Dias da Costa |
| Support Opportunities: | Scholarships in Brazil - Doctorate |
| 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 |