Energy-Efficient Computation Task Splitting for Edge Computing-Enabled Vehicular Networks

In this paper, we develop the energy-efficient resource allocation scheme for an edge computing-enabled vehicular network. We first introduce the novel prescheduled task splitting and offloading scheme, which splits the vehicle's task into several subtasks and offloads to multiple road side units (RSUs), located ahead along the route. We then formulate the energy minimization problem subject to the communication performance and computation capabilities of the RSUs, and the deadline constraints to optimally split the task and allocate resources at the RSUs. We show that the optimization problem is a convex optimization problem and derive the closed form optimal solutions for the task splitting, the transmission power allocation, the CPU frequency allocation, and the transmission time allocation. Finally, through numerical results, by analyzing the impact of network parameters on the total energy consumption, we verify that our proposed scheme consumes lower energy than baseline schemes.