A Reliable and Efficient Fog‐Based Architecture for Autonomous Vehicular Networks

Advancements in the field of artificial intelligence, sensor technologies, and autonomous or self‐driving vehicles have made it possible to sense the surroundings of vehicles in real time. This is achieved by the combination of several different techniques, including radar, GPS, computer vision, Internet of Things, cloud, and fog. Vehicular ad hoc networks (VANETs) offer various services, such as traffic monitoring, data passing through cars, road safety for vehicles, and comfort. Due to the arrival of the autonomous vehicles (AVs), data traffic over networks has increased severely. The excessive use of in‐vehicle mobiles and other smart devices has affected the latency and bandwidth of the network in the cloud. In case of VANETs, connecting everything to the cloud affects the latency, resulting in delays that could be life‐threatening. As the safety of human life is the top priority, no risks can be tolerated in this matter. In this chapter, we propose a Fog‐based architecture to minimize the latency and bandwidth utilization in the VANETs. To evaluate the performance of the proposed architecture, we used iFogSim to implement both the fog‐based and the cloud‐based architectures. We ran multiple simulations of the scenario created on both of the architectures. The results of the simulation showed that the proposed fog‐based architecture is not only helpful to minimize the latency, it also consumes less bandwidth and is more scalable than the cloud‐based network. Moreover, the low latency and bandwidth consumption also depict the reliability and efficiency of the proposed methodology for autonomous vehicular networks (AVNs).