A novel angle-based clustering algorithm for vehicular ad hoc networks

Abstract

A vehicular ad hoc network (VANET) is a mobile network in which vehicles acting as moving nodes communicate with each other through an ad hoc wireless network. VANETs have become the core component of Intelligent Transportation Systems (ITS) which aim to improve the road safety and efficiency. Only if the communication scheme used in a VANET is stable can these aims be achieved. Frequent changes in network topology and breaks in communication raise challenging issues in the design of communication protocols for such networks. Currently, clustering algorithms are being used as the control schemes to reduce changes in VANET topologies. However, the design of a clustering algorithm becomes a difficult task in VANETs when there are many road segments and intersections. In this work, we propose an Angle-based Clustering Algorithm (ACA), which exploits the angular position and the direction of the vehicles to select the most stable vehicles that can act as cluster heads for a long period of time. The simulation results reveal that ACA significantly outperforms other clustering protocols in terms of cluster stability.