An Adaptable Mobility-Aware Clustering Algorithm in vehicular networks

The forthcoming Intelligent Transportation System aims to achieve safety and productivity in transportation using vehicular ad hoc networks (VANETs) to support the communications system required. Currently, some clustering approaches have been proposed to improve the performance of VANETs due to their dynamic nature, high scalability and load balancing results. However, the host mobility and the constantly topology change continue to be main problems of this technique due to the lack of models which represent the vehicular behavior and the group mobility patterns. Therefore, we propose an Adaptable Mobility-Aware Clustering Algorithm based on Destination positions (AMACAD) to accurately follow the mobility pattern of the network prolonging the cluster lifetime and reducing the global overhead. In an effort to show the efficiency of AMACAD, a set of simulation was executed. The obtained results reveal an outstanding performance in terms of the lifetime of the cluster heads, lifetime of the members and the re-affiliation rate under varying speeds and transmission ranges.