RoVAN: A Rough Set-based Scheme for Cluster Head Selection in Vehicular Ad-hoc Networks

Abstract

Vehicular ad-hoc networks (VANET) have been used in many application and services ranging from intelligent transportation to e-healthcare. However, in VANET, one of the major challenges is the cluster head (CH) selection as it influences vehicle mobility, transmission range, and inter-vehicle distance. However, for stable cluster formation in VANET, it is essential that these constraints must be considered while selecting the CH. However, with an increase in the number of nodes in a cluster, the existing CH selection schemes become inefficient which leads to a substantial increase in the execution time for aforementioned applications. Hence, to address this issue, a rough set-based scheme is presented in this paper for CH selection with an aim to reduce the CH selection time. To achieve this aim, the concept of cluster member fields (which represents similar nodes) has been used which reduces the number of nodes participating in the CH selection. The proposed scheme has been evaluated with respect to various performance metrics such as CH selection time and CH reliability (on the basis of vehicle density and average velocity of vehicles in the clusters). The results obtained confirm that the CH selection time in the proposed scheme is less and CH reliability in more as compared with an existing scheme.