Traffic Routing-Based Computation Offloading in Cybertwin-Driven Internet of Vehicles for V2X Applications

Abstract

With the rapid development of the Internet of Vehicles (IoV), a lot of Vehicle-to-Everything (V2X) applications have sprung up. To tackle the conflict between the resource-hungry V2X applications and the resource-constrained vehicles, most works focus on the computation offloading problem, which is significant to V2X applications by bringing computation tasks from the vehicles to the edge or cloud infrastructure. However, the dynamic network conditions caused by the mobility of vehicles will bring task migration and huge additional costs, resulting in poor latency performance. Motivated by the aforementioned problem, a traffic routing-based computation offloading scheme in cybertwin-driven IoV for V2X applications is proposed, in which cybertwin represents the network hardware devices and the network software functions. Moreover, according to the cybertwin-driven IoV network architecture, the traffic routing-based computation offloading problem is formulated. Finally, to avoid the inconsistency between the data transmission direction and the vehicle’s movement direction, the enhanced Heterogeneous Earliest Finish Time (eHEFT) algorithm is designed, which introduces the gradient routing into the traditional HEFT algorithm. Performance evaluation results validate that the proposed joint optimization scheme is indeed capable of reducing latency.