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Supervisor of Master's Candidates

School/Department:School of computer science and information egineering

Administrative Position:党支部书记

Education Level:With Certificate of Graduation for Doctorate Study


Degree:Doctoral degree


Alma Mater:Hefei University of Technology

Discipline:Computer Applications Technology




Education Level:With Certificate of Graduation for Doctorate Study

Alma Mater:Hefei University of Technology

Paper Publications

New Affinity Propagation ClusteringAlgorithm for V2V-Supported VANETs

DOI number:10.1109/ACCESS.2020.2987968
Abstract: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.
Co-author:Baishun Guo,Yang Lu,Zengwei Lyu
First Author:Xiang Bi
Indexed by:Journal paper
Correspondence Author:Lei Shi*
Document Type:J
Page Number:71405-71421
ISSN No.:2169-3536
Translation or Not:no
Date of Publication:2020-08-01
Included Journals:SCI