Currently, researchers are focusing on efficient applications and resource scheduling strategies in vehicular edge computing(VEC) environments, however, the real-world validation of these applications and strategies is often limited by cost and time and cannot be performed quickly and efficiently. The emergence of edge/fog computing simulators such as iFogSim2 reduces the cost of experiments. However, the connection switching and resource allocation requirements of high-speed moving vehicles pose challenges to the application of edge/fog computing simulators under VEC. Therefore, this paper improved iFogSim2 by designing VECSim, a VEC environment simulator that supported high-speed mobility. It integrated open-source base station data and constructed vehicle trajectory datasets so that researchers can focus on resource allocation strategies. Firstly, to simplify the experimental steps, this paper improved the mobile trajectory data parsing module and adapted the vehicle trajectory data generated by Simulation of Urban Mobility(SUMO), a microscopic transportation simulation software. Secondly, this paper modeled distributed applications under VEC based on the distributed data flow model and provided a service migration benchmark policy algorithm. In addition, VECSim introduced a time-performance optimization method to accelerate the simulation event processing by parallelizing the operation, which improved the time performance of the simulation tool. Experiments show that compared with similar service migration algorithms in iFogSim2, the proposed service migration algorithm exhibits good stability under the validation of large-scale motor vehicle trajectory dataset, and the time-performance optimization method achieves a 5.3% performance improvement in execution time. Code is available: https: //github. com/LiuZiyuan-CS/VECSim.

[2023-12-08] Accepted Paper /doc/2023.09.0429/v1

[2024-05-05] Printed Article /doc/2023.09.0429/v2