A Low-Latency and Massive-Connectivity Vehicular Fog Computing Framework for 5G

Future 5G vehicular applications pose strict requirements on latency and reliability. In this paper, we propose a low-latency massive-connectivity vehicular fog computing framework to relieve the overload on the base station and reduce the processing delay during the peak time. The computation tasks of user equipments (UEs) are offloaded to nearby vehicles with under-utilized computation resources. Furthermore, in order to minimize the total delay of the network, a two-dimensional matching algorithm was proposed to deal with the task assignment problem between vehicular fog nodes and UEs. Finally, we validate the proposed algorithm on a realistic road topology. Simulation results demonstrate that the proposed algorithm can approach the optimal performance with a much lower complexity.