基于改进的混合遗传算法的车联网任务卸载策略研究

doi:10.11959/j.issn.1000-436x.2022188

Abstract

Abstract:

Aiming at the problem of unreasonable resource allocation caused by the unloading decision in the multi-vehicle and multi-server IoV scenario, a two-stage heuristic IoV task offloading strategy was proposed.This strategy used the improved hybrid genetic algorithm (IHGA) and the improved artificial fish swarm algorithm (AFSA), combined with the system’s internal average overhead, delay and energy consumption requirements, the two improved algorithm was used for multiple iterations to achieve optimal resource allocation in the process of task unloading.The simulation results show that the proposed scheme can effectively reduce the system internal overhead and improve the task offloading efficiency compared with the benchmark scheme.

Key words: Internet of vehicles, offloading, genetic algorithm, artificial fish swarm algorithm

CLC Number:

TN929.5

Yuliang CONG, Wenxi SUN, Ke XUE, Zhihong QIAN, Mianshu CHEN. Research on task offloading strategy of Internet of vehicles based on improved hybrid genetic algorithm[J]. Journal on Communications, 2022, 43(10): 77-85.

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