dacosta2022efficient
Joahannes B. D. da Costa, Allan M. de Souza, Denis Rosário, Christoph Sommer and Leandro Aparecido Villas, "Efficient Pareto Optimality-based Task Scheduling for Vehicular Edge Computing," Proceedings of 96th IEEE Vehicular Technology Conference (VTC 2022-Fall), London, United Kingdom, September 2022.
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 use of these computational re- sources via task scheduling. An efficient task scheduler needs to 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.
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Contact
- Joahannes B. D. da Costa
- Allan M. de Souza
- Denis Rosário
- Christoph Sommer
- Leandro Aparecido Villas
BibTeX reference
@inproceedings{dacosta2022efficient,
author = {da Costa, Joahannes B. D. and de Souza, Allan M. and Ros{\'{a}}rio, Denis and Sommer, Christoph and Aparecido Villas, Leandro},
title = {{Efficient Pareto Optimality-based Task Scheduling for Vehicular Edge Computing}},
booktitle = {96th IEEE Vehicular Technology Conference (VTC 2022-Fall)},
address = {London, United Kingdom},
doi = {10.1109/VTC2022-Fall57202.2022.10013029},
isbn = {978-1-66545-468-1},
issn = {2577-2465},
month = {September},
publisher = {IEEE},
year = {2022},
}
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