AI-Based Effective Communication in Software-Defined VANET: A Study

The frequency of roadside accidents is rising quickly along with the number of automobiles. The driver’s irresponsibility is to blame for the bulk of these collisions. The current communication networks in the automotive ad hoc networks face enormous obstacles due to the constantly rising traffic, numerous delay-sensitive services, and energy-constrained needs. Researchers from all over the world are constantly creating new protocols and architecture for intelligent transportation systems. As a result, many nations are increasingly embracing and investing heavily in vehicular ad hoc networks (VANET) in order to assure the safety of drivers. On the other hand, before VANET technology is widely used, there are a number of problems in this area that need to be fixed. Numerous attacks may take place in the event of low or no security, which could impact the system’s dependability and effectiveness. Software-Defined Networking technology (SDN) was introduced to increase the effectiveness of VANET systems. In this article, a short study on Intelligent reflecting surface (IRS) and artificial intelligence (AI)-enabled energy-efficient communication solution for SDN vehicular Network is explained. SDN-based VANET was the quick term for this method. The data transmission in AI-based IRS and the three planes in this framework are also explained in this paper. The cluster head selection of a vehicle and communication between vehicle to vehicle are also provided in this article. To enhance vehicular communication, an IRS-aided data transfer is suggested.