An AI-Based Transmission Power-Control Certificate Omission in Vehicular Ad-Hoc Networks

Abstract

Fundamental to achieving cooperative awareness amongst vehicles is the periodic dissemination of beacons. However, ensuring the secure dissemination of these beacons has over the years become an issue of importance as these beacons often than not contain some level of safety-critical information which are susceptible to attack. Consequently, researchers have proposed in the literature the use of digital certificates issued by a trusted authority as means of ensuring beacon authenticity and the use of a digital signature as a means of ensuring beacon integrity. Nonetheless, this security method is characterized by an increase in communication overhead caused by the increase in the beacon payload size. To address this issue, some researchers have in recent years proposed approaches like the Neighbor-based Certificate Omission (NbCO) and Transmission Power-control Certificate Omission (TPCO) strategy that uses a certificate omission technique to control channel congestion. Upon evaluation, these strategies have proved to be promising as they focus on tuning the beacon payload size which has a direct impact on the communication channel load and hence reducing channel congestion. Despite the benefits of these strategies, they face the general issue of how to maintain a steady and minimized number of Cryptographic Packet Loss (CPL) and Network Packet Loss (NPL) even as the traffic congestion situation in a vehicular environment increases (i.e.: CPL are beacons dropped because they are unverifiable due to the absence of a corresponding certificate and NPL are the beacons dropped over the network due to congestion).

Therefore, we propose in this work an Artificial Intelligence-based Transmission Power-Control Certificate Omission (AI-TPCO) scheme which allows vehicles to demonstrate an efficient control over communication channel load by intelligently tuning their transmission power using fuzzy logic and also reactively adapting their beacon size using NbCO strategy. Our obtained simulation results prove that our proposed AI-TPCO scheme is able to attain a steady and minimized number of CPL and NPL even as the traffic congestion situation in a vehicular environment increases and as such maximizing cooperative awareness amongst vehicles.