Reliability-Aware Joint Optimization for Cooperative Vehicular Communication and Computing

This paper comprehensively discusses the cooperative communication and computation of vehicular system. Based on the cooperative transmission, an stochastic model of vehicle-to-vehicle (V2V) communication reliability is established using probability theory. Furthermore, the computation reliability is defined as a new metric for computation offloading, and a vehicle computational performance evaluation model is also established. In order to effectively compute the required data, we combine V2V communication and vehicle computing to further characterize the coupling reliability of cooperative communications and computation systems. In addition, we propose a virtual queue model that combines queue length and vehicle privacy entropy to optimize partitioning. Finally, considering the amount of processing data and cut-off time of vehicle applications, we establish the optimal partition model of vehicle computing with the goal of maximizing the coupling reliability, and propose the coupling-oriented reliability calculation for vehicle collaboration using dynamic programming methods. Simulations show that the proposed scheme outperforms traditional approaches in terms of coupling reliability and completion rate. In addition, the allocation between local computing and data offloading is controlled by the server's privacy perception of collaboration events.