基于软件定义车载网络的QoS 路由规划研究  

Research on QoS Routing Planning Based on Software-Defined Vehicular Network

作　　者：崔峻玮 翟亚红[2] Cui Junwei;Zhai Yahong(School of Computer and Artifical Intelligence,Lanzhou College of Information Science and Technology,Lanzhou 730300;School of Electrical&Information Engineering,Hubei University of Automotive Technology,Shiyan 442002)

机构地区：[1]兰州信息科技学院计算机与人工智能学院,兰州730300 [2]湖北汽车工业学院电气与信息工程学院,十堰442002

出　　处：《汽车技术》2025年第1期26-32,共7页Automobile Technology

基　　金：湖北省教育厅科研计划重点项目(D20211802);湖北省科技厅计划项目(2022BEC008)。

摘　　要：为了提高车载网络中的数据传输速率和保障业务的QoS需求,结合软件定义车载网络(SDVN)技术,设计了一种基于SDVN的深度强化学习QoS路由算法。该算法可以实现智能化控制和优化管理车载网络中的数据传输,以保证车载网络流量的控制、分配和监控,提高车载数据传输质量和效率。试验结果表明,该路由算法能较好地降低车载网络的时延,与传统路由算法相比,该算法具有更好的优化性能。With the increasing applications of new technologies such as smart driving,autonomous driving and Internet connectivity,traditional in-vehicle networks are difficult to meet the Quality of Service(QoS)demands of diverse applications.In order to improve the data transmission rate and guarantee the QoS demand of services in the in-vehicle network,a deep reinforcement learning QoS routing algorithm based on SDVN is designed in combination with Software-Defined Vehicular Network(SDVN)technology.The algorithm can realize intelligent control and optimized management of data transmission in the in-vehicle network to ensure the control,distribution and monitoring of in-vehicle network traffic and improve the quality and efficiency of in-vehicle data transmission.The experimental results show that the routing algorithm can better reduce the delay of the in-vehicle network and has better optimization performance compared to the traditional routing algorithm.

关 键 词：软件定义车载网络 服务质量 路由规划 深度强化学习 

分 类 号：TP393[自动化与计算机技术—计算机应用技术] U462.2[自动化与计算机技术—计算机科学与技术]