The rapid growth of the automotive industry has exacerbated the conflict between the complex traffic environment, increasing communication demands, and limited resources. Given the imperative to mitigate traffic and network congestion, analyzing the performance of Internet of Vehicles (IoV) mesh networks is of great practical significance. Most studies focus solely on individual performance metrics and influencing factors, and the adopted simulation tools, such as OPNET, cannot achieve the dynamic link generation of IoV mesh networks. To address these problems, a network performance analysis model based on actual switches is proposed. First, a typical IoV mesh network architecture is constructed and abstracted into a mathematical model that describes how the link and topology changes over time. Then, the task generation model and the task forwarding model based on actual switches are proposed to obtain the real traffic distribution of the network. Finally, a scientific network performance indicator system is constructed. Simulation results demonstrate that, with rising task traffic and decreasing node caching capacity, the packet loss rate increases, and the task arrival rate decreases in the network. The proposed model can effectively evaluate the network performance across various traffic states and provide valuable insights for network construction and enhancement.

翻译：汽车产业的快速发展加剧了复杂交通环境、日益增长的通信需求与有限资源之间的矛盾。鉴于缓解交通与网络拥堵的迫切需求，分析车辆自组织网状网络的性能具有重要的现实意义。现有研究多集中于单一性能指标及影响因素，且采用的仿真工具（如OPNET）无法实现车辆自组织网状网络的动态链路生成。为解决上述问题，本文提出一种基于实际交换设备的网络性能分析模型。首先构建典型的车辆自组织网状网络架构，并将其抽象为描述链路与拓扑随时间演化的数学模型。随后提出基于实际交换设备的任务生成模型与任务转发模型，以获取真实的网络流量分布。最后构建科学的网络性能指标体系。仿真结果表明：随着任务流量的增加与节点缓存容量的降低，网络丢包率上升，任务到达率下降。所提模型能有效评估不同流量状态下的网络性能，为网络建设与优化提供重要参考依据。