RIS assisted Cooperative Computation Offloading for Autonomous Vehicle in Mobile Edge Computing

Vehicular networks are a crucial component aimed to revolutionize the transportation system through the integration of several services and technologies including autonomous driving, dynamic routing, real-time traffic monitoring, and onboard entertainment systems. These services necessitate robust computational resources, seamlessly fulfilled by mobile edge computing (MEC) trough the roadside units (RSUs). MEC excels in offering low-latency with real-time data access, which is critical for these applications. As we gear up for the advent of 6G networks, which will operate at millimeter-wave and terahertz frequencies, the challenge of signal loss becomes significant. To this end, this paper propose a novel 6G latency aware computational offloading framework that strategically deploys Reconfigurable Intelligent Surfaces (RIS) between autonomous vehicles and RSUs. Our approach leverage cooperative interactions among RSUs, which enhances overall service performance and significantly reduces latency. Both of these factors are crucial for providing efficient MEC environment in vehicular networks. Our proposed method has been implemented and tested where the results shows that our approach achieves 5 to 7 seconds reduction in time delay compared to the state-of-the-art approaches.