Energy-Efficient Cooperative Offloading for Edge Computing-Enabled Vehicular Networks

Edge computing technology has great potential to improve various computation-intensive applications in vehicular networks by providing sufficient computation resources for vehicles. However, inappropriate task offloading roadside units (RSUs) can lead large energy consumption, which will result negative economic, environmental, and performance impacts. Therefore, this paper, we develop the energy-efficient cooperative scheme edge computing-enabled networks. We first establish a novel model multiple RSUs given batch of moving vehicles, different from existing works that consider single vehicle only or static users. Then, total minimization optimizing splitting ratio, resource, communication is challenging non-convex problem, provide optimal solutions multi-vehicle case single-vehicle case, respectively. Furthermore, extend our proposed one more realistic scenario (i.e., online scenario), where batches vehicles sequentially approach RSUs. Finally, through numerical results, impact network parameters on consumption analyzed, verify solution consumes lower than baseline schemes.