Enabling low-latency applications in vehicular networks based on mixed fog/cloud computing systems

In order to support delay-sensitive applications of vehicle equipment (V-UE) in the Internet-of-Vehicles (IoV) systems, it is necessary to allow V-UEs to offload their computationally intensive applications to a cloud or fog computing server. Existing works mainly focused on minimising the transmission and processing delays while ignoring the mobility of V-UEs and/or the queueing delays at the cloud or fog servers. In this paper, we consider a vehicular network supported by a mixed fog and cloud computing system, where the queues at the fog node (FN) and the cloud centre are modelled following the M/M/1 and M/M/C queueing models, respectively. To minimise the maximum service delay (which includes the transmission delay, queueing delay and processing delay) among the V-UEs, we propose to jointly optimise the offloading decisions of all V-UEs and the computation resource allocation at the FN while considering the V-UEs’ mobility and queueing delays at the FN and cloud centre. This is achieved by devising a fireworks algorithm-based offloading decision optimisation algorithm in conjunction with a bisection method-based FN computation resource allocation scheme. Simulation results demonstrate that our proposed algorithm achieves a much lower maximum service delay than the benchmarks.