An Efficient Weight-Based Clustering Algorithm using Mobility Report for IoV

Abstract

Internet of Vehicles (IoV) has recently been the focus of many researchers as a new paradigm of Intelligent Transportation System (ITS). Because of various factors, such as high mobility, scalability and communication overhead, the proposal of an efficient application is one of the important challenging issues in IoV. Clustering have proven to be an effective technique to improve significantly the performances of the vehicular network. In this regard, the present work introduces a new Efficient Weight-based Clustering Algorithm using Mobility Report (WECA-MR) for IoV, which aims to increase the stability of clusters and reduce communication overhead. To elect the Cluster Heads (CHs), the proposed scheme uses both classic weighted metrics such as degree, average distance and a new metric introduced by our proposed scheme called Mobility Report (MR). It is a metric that combines mobility metrics: relative velocity and relative acceleration. This work suggests that the unavailability of CH could be minimized when the main CH and another Backup CH (BCH) are elected. We compare the performance of the proposed scheme to MOSIC protocol using network simulator NS-2 and VanetMobiSim integrated environment, in order to validate the performances of the proposed scheme.