Performance Analysis of Internet of Vehicles Mesh Networks Based on Actual Switch Models

TL;DR

The paper tackles the challenge of analyzing IoV mesh network performance under highly dynamic topology and traffic demands by introducing an actual switch based modeling framework. It constructs a dynamic topology with V2V and V2I channels, develops port routing and task forwarding models that reflect real switch behavior, and builds a multi-metric performance indicator system. Through simulations, it demonstrates how task ingress QoS, node caching capacity, and vehicle density jointly affect packet loss, task arrival rate, and load metrics, providing insights for load balanced routing and resource allocation. The work offers a practical framework for evaluating IoV networks under diverse traffic states, enabling more informed network design and management choices.

Abstract

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.

Figures (11)

• Figure S1: The architecture of IoV mesh network.
• Figure S2: Simulation scenario.
• Figure S3: IoV mesh network model.
• Figure S4: Port route model.
• Figure S5: Single-task forwarding model.