基于改进式免疫遗传算法的车联网任务卸载方案  

Task offloading scheme of Internet of Vehicles based onimproved immune genetic algorithm

作　　者：陈发堂[1] 李璐 张若凡 Chen Fatang;Li Lu;Zhang Ruofan(School of Communication and Information Engineering,Chongqing University of Posts and Telecommunications,Chongqing 400065,China)

机构地区：[1]重庆邮电大学通信与信息工程学院,重庆400065

出　　处：《计算机应用研究》2024年第2期558-562,共5页Application Research of Computers

基　　金：重庆市自然科学基金资助项目(cstc2021jcyj-msxmX0454)。

摘　　要：为了解决车联网场景下卸载决策和资源分配不合理的问题,提出了一种改进的启发式车联网任务卸载策略。该策略利用改进式的双种群免疫遗传算法(IDP-IGA),在保留了精英种群的同时引入了自适应移民算子,并在满足车辆最大容忍时延和路侧单元最大可分配资源的前提下,优化系统的时延-能耗开销。仿真结果表明,所提算法具有良好收敛性,与传统算法和遗传-粒子群优化算法相比,能够显著降低系统的时延-能耗开销,在任务卸载过程中实现最优的资源分配方案。In order to solve the problem of unreasonable offloading decision and resource allocation in the scenario of IoV,this paper proposed an improved heuristic task offloading strategy of IoV.This strategy used the improved dual-population immune genetic algorithm(IDP-IGA),introduced the adaptive immigration operator while retaining the elite population,and optimized the delay-energy consumption overhead of the system under the premise of satisfying the maximum tolerance delay of the vehicle and the maximum allocable resources of the roadside unit.The simulation results show that the proposed algorithm has good convergence,and compared with the traditional algorithm and genetic-particle swarm optimization algorithm,it can significantly reduce the delay-energy consumption overhead of the system,and realize the optimal resource allocation scheme in the process of task offloading.

关 键 词：任务卸载 车联网 资源分配 免疫遗传算法 

分 类 号：TN929.5[电子电信—通信与信息系统]