移动边缘计算环境下基于改进GPSR的VANET路由算法

针对车辆自组织网络(VANET,vehicular ad-hoc network)中现有路由协议存在的路由选择错误、丢包率较高、服务质量低等问题,提出了移动边缘计算环境下,结合改进贪婪周边无状态路由(GPSR,greedy perimeter stateless routing)和自适应链路质量评估的VANET路由算法;首先,结合边缘计算构建了VANET通信模型,对其车辆位置和速度进行系统的理论分析;将边缘计算架构应用于VANET能够有效缓解计算量大、与车辆有限且不均的资源分布之间的矛盾;然后,提出了基于节点移动速度和节点间距离的改进GPSR协议,通过自适应链路稳定性和链路传递速率评估来选择合适的中继节点,动态更新链路;通过SUMO仿真平台对路由算法的性能进行评估,实验结果表明,相对于其他算法,所提算法受车辆密度、交通流以及车辆相对速度的影响较小,且提高了分组传送率(车辆数为300时传送率达到92%),减少端到端延迟(交通流为5时延迟降低到1.5 s),从而降低了通信开销。

VANET Routing Algorithm Using Improved GPSR and Adaptive Link Quality Assessment

Aiming at the problems of the existing routing protocols in vehicular ad hoc network (VANET), such as wrong routing, high packet loss rate and low quality of service, this paper proposes a VANET routing algorithm in the mobile edge computing environment, which combines the improved greedy perimeter stateless routing (GPSR) and adaptive link quality assessment. First of all, combined with edge computing, the VANET communication model is constructed, and the vehicle position and speed are analyzed systematically. The application of edge computing architecture in VANET can effectively alleviate the contradiction between large amount of computing and limited and uneven distribution of resources. Then, an improved GPSR protocol based on the mobile speed of nodes and the distance between nodes is proposed. Through the adaptive link stability and link transfer rate evaluation, the appropriate relay nodes are selected and the link is dynamically updated. The performance of the routing algorithm is evaluated by SUMO simulation platform. The experimental results show that compared with other algorithms, the proposed algorithm is less affected by vehicle density, traffic flow and vehicle relative speed, and improves packet transmission rate (92% when the number of vehicles is 300), reduces end-to-end delay (1.5s when the traffic flow is 5), thus reducing the communication cost.