VFogSim: A Data-driven Platform for Simulating Vehicular Fog Computing Environment
Edge/fog computing is a key enabling technology in 5G and beyond for fulfilling the tight latency requirements of emerging vehicle applications, such as cooperative and autonomous driving. Vehicular Fog Computing (VFC) is a cost-efficient deployment option that complements stationary fog nodes with mobile ones carried by moving vehicles. To plan the deployment and manage the VFC resources in the real world, it is essential to take into account the spatio-temporal variations in both demand and supply of fog computing capacity and the trade-offs between achievable Quality-of-Services and potential deployment and operating costs. Concerning the complexity and the economic load of real-world measurements, simulation becomes a better option at the early research phase to validate capacity and resource management solutions in various urban environments. The existing simulation platforms cannot provide a realistic techno-economic investigation to analyze the implications of VFC deployment options, due to the simplified network models in use, the lack of support for fog node mobility, and limited testing scenarios. In this paper, we propose an open-source simulator VFogSim that allows real-world data as input for simulating the supply and demand of VFC in urban areas. It follows a modular design to evaluate the performance and cost-efficiency of different deployment scenarios under various vehicular traffic models, and the effectiveness of the diverse network and computation schedulers and prioritization mechanisms under user-defined scenarios. Compared with the existing edge/fog computing simulators, such as IFogSim, IoTSim, and EdgeCloudSim, to the best of our knowledge, our platform is the first one that supports the mobility of fog nodes and provides realistic modeling of V2X in 5G and beyond networks in the urban environment. Furthermore, we validate the accuracy of the platform using a real-world 5G measurement and demonstrate the functionality of the platform taking VFC capacity planning as an example.
Academy of Finland under grant number 317432 and 318937.
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ORCID of Submitting Author0000-0002-3971-8314
Submitting Author's InstitutionAalto University
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