TACA: Trust Aware Clustering using ACO for Secure and Reliable Vehicular Ah hoc Network Routing

Abstract In the modern era, the Vehicular Ad-hoc Network (VANET) received significant attention for information sharing among the societies. The emerging Internet of Things (IoT) for smart city perspective boosts the development of VANET based applications such as road safety and Intelligent Transport System (ITS). The efficiency of such networks is a widely studied research problem. The clustering has shown an efficient technique to address the challenges of VANET QoS and computational efficiency. The vehicles are grouped according to certain conditions to form the cluster. In this way, the entire network divides into different clusters. Each cluster consists of limited vehicles with its leader called Cluster Head (CH). But the major challenge for VANET clustering has related to the stability of the cluster. Due to high network dynamics, the unreliability for CH selection and data relaying becomes a security threat in VANET. To address such a security threat of VANET clustering, we proposed Trust-Aware Clustering using Ant Colony Optimization (TACA) protocol. For each cluster, an ACO-based optimal CH selection algorithm applying different trust components of the vehicle. The ACO solves the problem of optimal CH selection with minimum control overhead and maximum CH lifetime. The optimal CH selected has been selected based on trust-aware ACO fitness function using the parameters such as vehicle speed, Degree of Connectivity (DoC), vehicle congestion, and Packet Relaying Probability (PRP). This mechanism enables clusters to select reliable CH to address the security concerns of VANET communications. The TACA protocol has been evaluated with recent similar methods, and the results demonstrate efficiency in terms of QoS and computational overhead of clustering.