Toward Response Time Minimization Considering Energy Consumption in Caching-Assisted Vehicular Edge Computing
Chaogang Tang, Chunsheng Zhu, Huaming Wu, Qing Li, Joel J. P. C. Rodrigues · IEEE Internet of Things Journal · 2021
The advent of vehicular edge computing (VEC) has generated enormous attention in recent years. It pushes the computational resources in close proximity to the data sources and thus, caters for the explosive growth of vehicular applications. Owing to the high mobility of vehicles, these applications are of latency-sensitive requirements in most cases. Accordingly, such requirements still pose a great challenge to the computing capabilities of VEC, when these applications are outsourced and executed in VEC. Against this backdrop, we propose a new mathematical model, which, respectively, generalizes the computation and communication models, and applies application-oriented caching into VEC in this article. Based on this model, a new strategy is further proposed to optimize the average response time of applications over an infinite time-slotted horizon for VEC. A long-term energy consumption constraint is imposed to guarantee the stability of the VEC system, and the Lyapunov optimization technology is adopted to tackle this constraint issue. Two greedy heuristics are put forward to help find the approximate optimal solution in the drift-plus-penalty-based algorithm. Extensive experiments have been conducted to evaluate the response time and energy consumption in the caching-assisted VEC. The simulation results have shown that the proposed strategy can dramatically optimize the average response time while satisfying the long-term energy consumption constraint.