Efficient Pareto Optimality-based Task Scheduling for Vehicular Edge Computing
Research output: Contribution to book/Conference proceedings/Anthology/Report › Conference contribution › Contributed › peer-review
Contributors
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.
Details
Original language | English |
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Title of host publication | 2022 IEEE 96th Vehicular Technology Conference, VTC 2022-Fall 2022 - Proceedings |
Place of Publication | London, United Kingdom |
Publisher | IEEE |
Number of pages | 6 |
ISBN (electronic) | 978-1-66545-468-1 |
ISBN (print) | 978-1-6654-5469-8 |
Publication status | Published - Sept 2022 |
Peer-reviewed | Yes |
Publication series
Series | IEEE Conference on Vehicular Technology (VTC) |
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ISSN | 1090-3038 |
External IDs
Scopus | 85147015985 |
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Bibtex | nsm-dacosta2022efficient |