VEC System for Vehicle-to-Vehicle Communication Task Offloading Strategy Research

In the context of Vehicle Edge Computing (VEC) systems, optimizing the long-term return of the system is crucial, taking into account factors such as transmission delay, access delay, computing delay, available computing capacity, and the heterogeneity of vehicles and tasks. This paper introduces a task offloading scheme for Vehicle-to-Vehicle (V2V) communication in VEC systems. The proposed approach involves a systematic vehicle screening process based on signal strength. Following the screening, a task offloading model, employing a Semi-Markov Decision Process (SMDP-BOVS) derived from the vehicle screening, is established. An iterative approach utilizing Bellman’s equation is then applied to approximate the optimal solution. Extensive simulations demonstrate that the algorithm model presented in this paper effectively enhances the system’s sustained reward, meeting the requirements of vehicle task offloading.