Improving Fairness and Performance in Resource Usage for Vehicular Edge Computing

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

Beitragende

Abstract

Vehicular Edge Computing (VEC) has emerged to offer cloud computing services closer to vehicular users by combining vehicles and edge computing nodes into Vehicular Clouds (VCs). In this scenario, an intelligent task scheduler must decide which VC will run which tasks, considering contextual aspects like vehicular mobility and tasks’ requirements. This is important to minimize both processing time and monetary costs. However, such direct optimization can lead to unfairness in resource usage, easily leading to (as we will show) decreased performance. Towards this end, in this work, we propose FARID, a task scheduling mechanism that considers contextual aspects of its decision process and applies a probabilistic selection function on VCs to balance the processing load and increase the fairness in the use of vehicular resources. Compared to state-of-the-art solutions, FARID has a higher level of fairness and can schedule more tasks while minimizing monetary costs and system latency.

Details

OriginalspracheEnglisch
Titel2023 IEEE 98th Vehicular Technology Conference, VTC 2023-Fall - Proceedings
ErscheinungsortHong Kong, China
Herausgeber (Verlag)IEEE
ISBN (elektronisch)9798350329285
PublikationsstatusVeröffentlicht - 1 Okt. 2023
Peer-Review-StatusJa

Externe IDs

Scopus 85181170908