A Center-Based Stable Evolving Clustering Algorithm With Grid Partitioning and Extended Mobility Features for VANETs
VANETs clustering is an emerging research topic that serves in the intelligent transportation systems of today's technology. It aims at segmenting the moving vehicles in the road environment into sub-groups named clusters, with cluster heads for enabling effective and stable routing. Most of th...
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| Vydané v: | IEEE access Ročník 8; s. 169908 - 169921 |
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| Hlavní autori: | , , , , , , |
| Médium: | Journal Article |
| Jazyk: | English |
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IEEE
2020
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
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| ISSN: | 2169-3536, 2169-3536 |
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| Abstract | VANETs clustering is an emerging research topic that serves in the intelligent transportation systems of today's technology. It aims at segmenting the moving vehicles in the road environment into sub-groups named clusters, with cluster heads for enabling effective and stable routing. Most of the VANETs clustering approaches are based on distributed models which make the decision of clusters creation lacking the global view of the vehicle's distribution and mobility in the environment. However, the availability of the LTE and long ranges of base station motivated researchers recently to provide center-based approaches. Unlike existing center-based clustering approaches of VANETs, this article uses the road segmenting phase named grid partitioning before providing summarized information to the clustering center. Furthermore, it presents an integrated approach as a combination of all the clustering tasks including assigning, cluster head selection, removing, and merging. Evaluation of the proposed approach named center-based evolving clustering based on grid partitioning (CEC-GP) is proven superior from the perspective of efficiency, stability, and consistency. An improvement percentage of the efficiency in (CEC-GP) over the benchmarks Center based stable clustering (CBSC) and evolving data clustering algorithm (EDCA) is 65% and 394% respectively. |
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| AbstractList | VANETs clustering is an emerging research topic that serves in the intelligent transportation systems of today's technology. It aims at segmenting the moving vehicles in the road environment into sub-groups named clusters, with cluster heads for enabling effective and stable routing. Most of the VANETs clustering approaches are based on distributed models which make the decision of clusters creation lacking the global view of the vehicle's distribution and mobility in the environment. However, the availability of the LTE and long ranges of base station motivated researchers recently to provide center-based approaches. Unlike existing center-based clustering approaches of VANETs, this article uses the road segmenting phase named grid partitioning before providing summarized information to the clustering center. Furthermore, it presents an integrated approach as a combination of all the clustering tasks including assigning, cluster head selection, removing, and merging. Evaluation of the proposed approach named center-based evolving clustering based on grid partitioning (CEC-GP) is proven superior from the perspective of efficiency, stability, and consistency. An improvement percentage of the efficiency in (CEC-GP) over the benchmarks Center based stable clustering (CBSC) and evolving data clustering algorithm (EDCA) is 65% and 394% respectively. |
| Author | Abdullah, Nihad Ibrahim Talib, Mohammed Saad Abas, Zuraida Abal Alamery, Thamer Ibrahim, Ali Jalil Mohammed, Ali Abdul-Jabbar Hassan, Aslinda |
| Author_xml | – sequence: 1 givenname: Mohammed Saad orcidid: 0000-0002-2316-9242 surname: Talib fullname: Talib, Mohammed Saad email: mohammed90.saad1@gmail.com organization: Center for Advanced Computing Technology, Faculty of Information and Communication Technology, Universiti Teknikal Malaysia Melaka, Melaka, Malaysia – sequence: 2 givenname: Aslinda orcidid: 0000-0002-8608-5329 surname: Hassan fullname: Hassan, Aslinda organization: Center for Advanced Computing Technology, Faculty of Information and Communication Technology, Universiti Teknikal Malaysia Melaka, Melaka, Malaysia – sequence: 3 givenname: Thamer surname: Alamery fullname: Alamery, Thamer organization: Police Academy, Ministry of Interior, Baghdad City, Iraq – sequence: 4 givenname: Zuraida Abal surname: Abas fullname: Abas, Zuraida Abal organization: Center for Advanced Computing Technology, Faculty of Information and Communication Technology, Universiti Teknikal Malaysia Melaka, Melaka, Malaysia – sequence: 5 givenname: Ali Abdul-Jabbar surname: Mohammed fullname: Mohammed, Ali Abdul-Jabbar organization: Center for Advanced Computing Technology, Faculty of Information and Communication Technology, Universiti Teknikal Malaysia Melaka, Melaka, Malaysia – sequence: 6 givenname: Ali Jalil surname: Ibrahim fullname: Ibrahim, Ali Jalil organization: Chamchamal Technical Institute, Sulaimani Polytechnic University, Sulaimanyah, Iraq – sequence: 7 givenname: Nihad Ibrahim surname: Abdullah fullname: Abdullah, Nihad Ibrahim organization: Center for Advanced Computing Technology, Faculty of Information and Communication Technology, Universiti Teknikal Malaysia Melaka, Melaka, Malaysia |
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| SubjectTerms | Algorithms center-based clustering Clustering Clustering algorithms Evolution evolving clustering grid based-clustering Intelligent transportation systems Measurement Partitioning Roads Stability criteria VANETs clustering Vehicular ad hoc networks |
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| Title | A Center-Based Stable Evolving Clustering Algorithm With Grid Partitioning and Extended Mobility Features for VANETs |
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