Cost Modeling and Configuration Optimization for Large-Scale VANET Co-Simulation

Vehicular Ad Hoc Network (VANET) traffic–network co-simulation is a foundational methodology for the engineering evaluation of vehicle-to-everything (V2X) protocols and cooperative Intelligent Transportation System (ITS) applications before field deployment. However, with research objectives and experimental conditions varying widely, existing studies still lack a systematic paradigm for parameter configuration and experimental workflows. As a result, researchers often rely on experience-based settings, which can bring high time and computational overhead, long experimental cycles, and limited reproducibility. To address these issues, this paper proposes a simulation cost modeling and configuration optimization methodology for traffic–network co-simulation. By profiling and structurally modeling key overheads, such as initialization and traffic- and network-side execution, we characterize how traffic, network, and control parameters jointly affect total simulation overhead. We formulate a minimum-cost configuration optimization model under constraints of statistical validity and experimental comparability. We further develop a configuration solving mechanism and a structured workflow for simulation experiment configuration to complement empirical tuning with a more systematic approach, thereby improving the reproducibility of simulation studies. The study is grounded in a representative urban road-network co-simulation scenario based on Simulation of Urban MObility (SUMO), Veins, and Objective Modular Network Testbed in C++ (OMNeT++). Simulation results show that the proposed method reduces simulation overhead while keeping conclusions on key performance metrics consistent, thereby providing a more efficient and statistically credible evaluation basis for application-oriented urban VANET studies related to traffic safety, transportation efficiency, and wireless-system performance.