Joint Task Offloading and Multi-Task Offloading Based on NOMA Enhanced Internet of Vehicles in Edge Computing

Abstract

With the rapid development of technology, the Internet of vehicles (IoV) has become increasingly important. However, as the number of vehicles on highways increases, ensuring reliable communication between them has become a significant challenge. To address this issue, this paper proposes a novel approach that combines Non-Orthogonal Multiple Access (NOMA) with a time-optimized multitask offloading model based on Optimal Stopping Theory (OST) principles. NOMA-OST is a promising technology that can address the high volume of multiple access and the need for reliable communication in IoV. A NOMA-OST-based IoV system is proposed to meet the Vehicle-to-Vehicle (V2V) communication requirements. This approach optimizes joint task offloading and resource allocation for multiple users, tasks, and servers. NOMA enables efficient resource sharing by accommodating multiple devices, whereas OST ensures timely and intelligent task offloading decisions, resulting in improved reliability and efficiency in V2V communication within IoV, making it a highly innovative and technically robust solution. It suggests a low-complexity sub-optimal matching approach for sub-channel allocation to increase the effectiveness of offloading. Simulation results show that NOMA with OST significantly improves the system’s energy efficiency (EE) and reduces computation time. The approach also enhances the effectiveness of task offloading and resource allocation, leading to better overall system performance. The performance of NOMA with OST under V2V communication requirements in IoV is significantly improved compared to traditional orthogonal multiaccess methods. Overall, NOMA with OST is a promising technology that can address the high reliability of V2V communication requirements in IoV. It can improve system performance, and energy efficiency and reduce computation time, making it a valuable technology for IoV applications.