A Stable Clustering Scheme Based on Adaptive Multiple Metric in Vehicular Ad-hoc Networks

Abstract

Vehicular Ad-hoc Networks (VANETs) are the special class of Mobile Ad-hoc Networks (MANETs) with high mobility and frequent changes of topology. Clustering is applied in VANETs to divide the network into smaller groups of mobile vehicles and improve routing, information dissemination and data gathering. In this paper, we propose a 2-layer stable clustering scheme based on adaptive multiple metric combining both the features of static and dynamic clustering methods. The cluster head is selected among the cluster members based on a new multiple metric called suitability value. It is derived from both mobility metrics such as relative speed, position and time to leave the road segment and Quality of Service metrics including available bandwidth, neighborhood degree and RSU link quality. Due to the proposed adaptive metric, the higher cluster stability as well as QoS is achieved. The simulation results clarify effectiveness of our proposed method in a highway scenario and show that our technique has better results and provides more stable cluster structure compared with the other related methods.