C-V2X based Offloading Strategy in Multi-Tier Vehicular Edge Computing System

Many emerging intelligent transportation services are latency-sensitive with heavy demand for computing resources, which can be handled by a multi-tier computing system composed of vehicular edge computing (VEC) servers in the roadside and micro servers carried by vehicles. In multi-tier VEC system, the offloading of vehicle-to-vehicle (V2V) can be supported using the Cellular Vehicle-to-Everything (C-V2X) links, through Uu or PC5 interfaces. In this work, we investigate the offloading and resource strategy in C-V2X enabled multi-tier VEC system. The successful transmission probability of PC5 interface is modeled to characterize the normalized transmission rate of C-V2X link. We aim to minimize the total system latency of the task processing to optimize the offloading ratio matrix and packet transmit frequency of the PC5 interface, and computation resource allocation of vehicles and VEC server. Due to the non-convex and variables coupling, the latency minimization problem is decomposed into two subproblems, i.e., resource allocation and offloading strategy subproblems, and propose a PC5 interface based greedy offloading (PC5-GO) algorithm. Specifically, for the resource allocation subproblem, we derive the closed expressions of packet transmit frequency of PC5 interface and CPU computation frequency at vehicle and VEC server. For the offloading strategy subproblem, the offloading ratio matrix is obtained by the proposed PC5-GO algorithm. Simulation results are provided that the proposed PC5-GO algorithm can significantly enhance the system performance compared with other benchmark schemes by 5.88% at least.