吉林大学学报（信息科学版）2025，Vol.43Issue(5)：944-952,9.
基于改进灰狼优化算法的车联网边缘计算卸载方案
Edge Computing Unloading Scheme for Internet of Vehicles Based on Improved Grey Wolf Optimization Algorithm
摘要
Abstract
In order to solve the problem that the Internet of Vehicles with limited computing power can not undertake a large number of real-time task computing,offloads vehicle tasks are introduced to the edge server for computing through MEC(Mobile Edge Computing),and a joint optimization scheme for the delay and energy consumption of vehicle task offloading is proposed based on the I-GWO(Improved Grey Wolf Optimizer).A computation offloading model constrained by computation delay,energy consumption,and edge server computing resources is established,and an offloading optimization problem with the goal of minimizing the total system consumption is proposed.By improving the GWO(Grey Wolf Optimizer),the I-GWO used to solve optimization problem.Simulation results show that the proposed scheme can effectively reduce the total system consumption,and the convergence performance of I-GWO is greatly improved compared to GWO.关键词
车联网/移动边缘计算/卸载策略/灰狼优化算法Key words
internet of vehicles/mobile edge computing/offloading strategy/grey wolf optimizer分类
电子信息工程引用本文复制引用
张光华,赵宇,卢为党..基于改进灰狼优化算法的车联网边缘计算卸载方案[J].吉林大学学报（信息科学版）,2025,43(5):944-952,9.基金项目
国家自然科学基金资助项目(62271447) （62271447）
