A Dynamic-Pricing-Based Offloading and Resource Allocation Scheme With Data Security for Vehicle Platoon

Abstract

With the accelerated growth of the Internet of Vehicles (IoV), secure and efficient task offloading of vehicle has emerged as a critical challenge, particularly in highway scenarios. Traditional mobile edge computing (MEC) solutions face significant limitations in these environments due to frequent link disruptions and the dynamic nature of vehicle movements. Platoon offloading is considered a feasible solution, to address these challenges, we propose a novel dynamic pricing-based task offloading and resource allocation scheme specifically tailored for vehicle platoons, integrating robust data security measures. Our scheme employs a Stackelberg game framework to model the interaction between task vehicles and platoon members (PMs), ensuring fair compensation for resource allocation while maintaining low latency. We introduce a personalized security layer utilizing advanced encryption standard (AES) encryption to safeguard platoon communications, a critical enhancement given the vulnerability of wireless channels. Our scheme not only proves the existence of a unique Nash equilibrium but also optimizes the utility for both task vehicles and PMs through a dynamic pricing-based Stackelberg game (DPSG) algorithm. Simulation results demonstrate that DPSG can substantially improve entire performance compared to other schemes, such as local execution, MEC offloading scheme, Hooke-Jeeves-based Stackelberg game algorithm, and reinforcement learning-based offloading optimal scheme.