A novel vehicular task deployment method in hybrid MEC

Abstract With the skyrocketing need for low-latency services on the Internet of Vehicles (IoV) and elastic cross-layer resource provisioning, multi-access edge computing (MEC) is considered a high-potent solution, which evolves from cloud and grid computing to meet the above needs in IoV scenarios....

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Bibliographic Details
Main Authors: Xifeng Xu, Yunni Xia, Feng Zeng, Fan Li, Hong Xie, Xiaodong Fu, Mengdi Wang
Format: Article
Language:English
Published: SpringerOpen 2022-12-01
Series:Journal of Cloud Computing: Advances, Systems and Applications
Subjects:
Online Access:https://doi.org/10.1186/s13677-022-00357-8
Description
Summary:Abstract With the skyrocketing need for low-latency services on the Internet of Vehicles (IoV) and elastic cross-layer resource provisioning, multi-access edge computing (MEC) is considered a high-potent solution, which evolves from cloud and grid computing to meet the above needs in IoV scenarios. Instead of considering single-point and monolithic IoV tasks, in this paper, we consider the IoV applications to be with structural properties and the supporting environment to be with a hybrid cloud-edge architecture. We develop a scheduling method that offloads tasks to the eNode or cloud according to their estimations of latest starting time. Simulative results clearly demonstrate that our method beat existing solutions in terms of average completion time, average waiting time, and in-time completion rate.
ISSN:2192-113X