Data dissemination in vehicle ad hoc networks using social behavior-based clustering

Vehicle ad hoc networks consist of a number of nodes, each equipped with wireless communication equipment. In these networks, the destination for some data is all the vehicles present in the network which is named data dissemination. Due to the rapid changes in the topology of these networks, the dissemination and delivery of messages to all vehicles in inter-vehicle networks is considered a significant challenge. Various methods have been proposed to overcome these challenges. Among the existing methods, clustering seems to be an appropriate approach because an entity called the cluster head is responsible for delivering packets to the nodes within the cluster. Several clustering methods have been introduced for such networks, based on metaheuristic algorithms and machine learning. However, considering the dynamic nature of vehicle networks, there is practically no time available for data collection and the execution of these algorithms. It appears that utilizing inherent information, such as social behaviors and characteristics that do not require data collection, can be suitable for clustering vehicles and selecting the cluster head. In this paper, a method based on social features is proposed, known as social clustering-based data dissemination. In this method, initially, a number of nodes are selected as cluster heads based on their social characteristics, and then other nodes connect to the cluster heads based on speed and degree of the clusters. Simulation results show that using social behaviors in clustering improves packet delivery by 15% and reduces the average delay by 10% in the network.