Efficient Pareto Optimality-based Task Scheduling for Vehicular Edge Computing

Publikation: Beitrag in Buch/Konferenzbericht/Sammelband/GutachtenBeitrag in KonferenzbandBeigetragenBegutachtung

Beitragende

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

OriginalspracheEnglisch
Titel2022 IEEE 96th Vehicular Technology Conference, VTC 2022-Fall 2022 - Proceedings
ErscheinungsortLondon, United Kingdom
Herausgeber (Verlag)IEEE
Seitenumfang6
ISBN (elektronisch)978-1-66545-468-1
ISBN (Print)978-1-6654-5469-8
PublikationsstatusVeröffentlicht - Sept. 2022
Peer-Review-StatusJa

Publikationsreihe

ReiheIEEE Conference on Vehicular Technology (VTC)
ISSN1090-3038

Externe IDs

Scopus 85147015985
Bibtex nsm-dacosta2022efficient

Schlagworte