Open AccessVehicular task scheduling strategy with resource matching computing in cloud‐edge collaboration
Author(s) -
Hu Fangyi,
Lv Lingling,
Zhang TongLiang,
Shi Yanjun
Publication year - 2021
Publication title -
iet collaborative intelligent manufacturing
Language(s) - English
Resource type - Journals
ISSN - 2516-8398
DOI - 10.1049/cim2.12023
Subject(s) - cloud computing , computer science , distributed computing , scheduling (production processes) , schedule , matching (statistics) , edge computing , task (project management) , enhanced data rates for gsm evolution , resource (disambiguation) , computer network , mathematical optimization , artificial intelligence , operating system , engineering , statistics , mathematics , systems engineering
Abstract In future transportation, on board unit (OBU) is a key component of connected vehicles with limited computing resources, and may not tackle the heavy computing burden from V2X networks. For these cases, we herein employ multi‐access edge cloud (MEC) and remote cloud to schedule the OBUs' tasks. This schedule tries to minimise the total completion time of all tasks and the number of computing units of the MEC server. We first introduce a multi‐objective optimisation model considering the tasks and cloud‐edge collaboration. Then, we propose a task scheduling strategy considering the resource matching degree for this model. In this strategy, we propose an improved hybrid genetic algorithm and employ the resource matching measure between the tasks and computing units in terms of computing, storage and network bandwidth resources to obtain better solutions for generations. The numerical results showed the effectiveness of our strategy.