A New Affinity Propagation ClusteringAlgorithm for V2V-Supported VANETs
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DOI码：10.1109/ACCESS.2020.2987968
发表刊物：IEEE ACCESS
摘要：Clustering is an efficient method for improving the communication performance of Vehicular Ad hoc NETworks (VANETs) that adopt Vehicle to Vehicle (V2V) communications. However, how to maximize the cluster stability while accounting for the high mobility of vehicles remains a challenging problem. In this paper, we first reconstruct the similarity function of the Affinity Propagation (AP) clustering algorithm by introducing communication-related parameters, so the vehicles with low relative mobility and good communication performance can easily be selected as cluster heads. Then, by formally defining three scaling functions, a weighted mechanism is designed to quantitatively assess the effect on the cluster stability when a vehicle joins it. Base on them, from the perspective of global balance, a new AP clustering algorithm for the whole clustering process is proposed. To ensure the validity of simulations, we use the vehicular mobility data generated on the realistic map of Cologne, Germany, and perform a series of simulations for eleven metrics commonly adopted in similar works. The results show that our proposed algorithm performs better than other algorithms in terms of the cluster stability, and it also effectively improves throughput and reduces packet loss rate of VANETs over the classical APROVE algorithm and the NMDP-APC algorithm.
合写作者：Baishun Guo,Yang Lu,Zengwei Lyu
第一作者：Xiang Bi
论文类型：期刊论文
通讯作者：Lei Shi*
学科门类：工学
文献类型：J
卷号：8
页面范围：71405-71421
ISSN号：2169-3536
是否译文：否
发表时间：2020-08-01
收录刊物：SCI