A Hybrid Backbone Based Clustering Algorithm for Vehicular Ad-Hoc Networks

Abstract

In recent years, Vehicular Ad-Hoc Networks (VANETs) have become an active area of research due to their applications in Intelligent Transportation System (ITS). By creating a vehicular network, vehicles can send warning messages to alert drivers in other vehicles about the dynamically varying road condition thus further improving human safety on roads. VANETs exhibits unique characteristic like dynamically changing topology that should be managed for managing the network for applications related to timely delivery of sensitive messages. Clustering is a most effective way of managing and stabilizing such networks. A stable clustering algorithm reduces the overhead of re-clustering and makes the network management task easier. In this paper a hybrid backbone based clustering algorithm for VANETs is proposed. The concept of number of links and vehicular mobility is used for cluster formation and cluster head selection. During cluster formation, nodes with relatively higher degree of connectivity, initially form a backbone that is designated as leadership. The leadership than participates in cluster-head election and efficient cluster re-organization using aggregate relative velocity of vehicles in the leadership. Simulation results show that the proposed algorithm exhibits comparable cluster stability in urban scenarios.