Secure and stable Vehicular Ad Hoc Network clustering algorithm based on hybrid mobility similarities and trust management scheme

Abstract Clustering is currently receiving great attention due to the emergence of Vehicular Ad-Hoc Network (VANET) technology. It is a challenging issue due to the high mobility of vehicles which leads to frequent disconnections and quality of service (QoS) degradation. In the literature, many clustering algorithms have been proposed and most of them attempt to achieve cluster stability and assume that all nodes are trusted. However, due to the important role of cluster heads, the election of a malicious or compromised node as a cluster head has dire consequences that may severely compromise the security and reliability of the network. In this paper, we propose a new approach that elects trustworthy cluster heads based on hybrid approach combining stability and trust factors. Unlike prior researches, in trust management we consider both communication capabilities and trust of data that vehicles exchange to improve security and reliability. We propose also a new adaptive trust function to assess the data trust between nodes according to the reported event's requirement in terms of trust severity unlike other schemes which use a static trust function. Moreover, we introduce a timer that reduces the control traffic during a clustering process by eliminating the competition of nodes to become cluster-head. Simulation results show that the proposed approach improves significantly the cluster stability while ensuring better vehicles cooperation and reliable data sharing compared to the latest clustering protocols proposed in VANET.