关键词: 车联网, 移动边缘计算, 卸载策略, 灰狼优化算法

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.

Key words: internet of vehicles, mobile edge computing, offloading strategy, grey wolf optimizer