A Stability-Based Clustering Scheme for Vehicular Networks
Dengyin Zhang, Min Zhang, Fei Ding, Shengbo Eben Li, Keqiang Li
Abstract
In vehicular ad-hoc networks (VANETs), vehicles need to report their dynamic information periodically to a nearby base station or roadside units. This high frequency communication often causes network congestion and adversely affect the connectivity of VANETs. In this paper, a stabilized clustering scheme is proposed to improve the information exchange efficiency of D2D enabled vehicular networks. The effectiveness of this scheme is compared with a movement consistency-based clustering algorithm in terms of the cluster head duration and cluster head change ratio. When selecting the cluster head, we have considered the relative velocity, link reliability and the number of neighbor nodes of the vehicle. The simulation results reveal that the proposed scheme has superior performance.