A New Affinity Propagation Clustering Algorithm for V2V-Supported VANETs
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...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2020-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/9066835/ |
| _version_ | 1818330593966948352 |
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| author | Xiang Bi Baishun Guo Lei Shi Yang Lu Lin Feng Zengwei Lyu |
| author_facet | Xiang Bi Baishun Guo Lei Shi Yang Lu Lin Feng Zengwei Lyu |
| author_sort | Xiang Bi |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-13T13:06:26Z |
| format | Article |
| id | doaj.art-69d7169201bc438faec483d7bf45b773 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-13T13:06:26Z |
| publishDate | 2020-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-69d7169201bc438faec483d7bf45b7732022-12-21T23:44:48ZengIEEEIEEE Access2169-35362020-01-018714057142110.1109/ACCESS.2020.29879689066835A New Affinity Propagation Clustering Algorithm for V2V-Supported VANETsXiang Bi0https://orcid.org/0000-0002-2736-4563Baishun Guo1Lei Shi2https://orcid.org/0000-0003-4042-592XYang Lu3Lin Feng4Zengwei Lyu5School of Computer Science and Information Engineering, Hefei University of Technology, Hefei, ChinaSchool of Computer Science and Information Engineering, Hefei University of Technology, Hefei, ChinaSchool of Computer Science and Information Engineering, Hefei University of Technology, Hefei, ChinaSchool of Computer Science and Information Engineering, Hefei University of Technology, Hefei, ChinaEngineering Research Center of Safety Critical Industrial Measurement and Control Technology, Ministry of Education, Hefei University of Technology, Hefei, ChinaSchool of Computer Science and Information Engineering, Hefei University of Technology, Hefei, ChinaClustering 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.https://ieeexplore.ieee.org/document/9066835/VANETsV2Vclusteringaffinity propagation |
| spellingShingle | Xiang Bi Baishun Guo Lei Shi Yang Lu Lin Feng Zengwei Lyu A New Affinity Propagation Clustering Algorithm for V2V-Supported VANETs IEEE Access VANETs V2V clustering affinity propagation |
| title | A New Affinity Propagation Clustering Algorithm for V2V-Supported VANETs |
| title_full | A New Affinity Propagation Clustering Algorithm for V2V-Supported VANETs |
| title_fullStr | A New Affinity Propagation Clustering Algorithm for V2V-Supported VANETs |
| title_full_unstemmed | A New Affinity Propagation Clustering Algorithm for V2V-Supported VANETs |
| title_short | A New Affinity Propagation Clustering Algorithm for V2V-Supported VANETs |
| title_sort | new affinity propagation clustering algorithm for v2v supported vanets |
| topic | VANETs V2V clustering affinity propagation |
| url | https://ieeexplore.ieee.org/document/9066835/ |
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