Tal, Irina ORCID: 0000-0001-9656-668X and Muntean, Gabriel-Miro ORCID: 0000-0003-2958-7979 (2021) Clustering and 5G-enabled smart cities: a survey of clustering schemes in VANETs. In: Research Anthology on Developing and Optimizing 5G Networks and the Impact on Society. IGI Global, USA, pp. 1012-1050. ISBN 9781799877080
Abstract
This chapter highlights the importance of Vehicular Ad-hoc Networks (VANETs) in the context of the 5Genabled smarter cities and roads, a topic that attracts significant interest. In order for VANETs and its associated applications to become a reality, a very promising avenue is to bring together multiple wireless technologies in the architectural design. 5G is envisioned to have a heterogeneous network architecture. Clustering is employed in designing optimal VANET architectures that successfully use different technologies, therefore clustering has the potential to play an important role in the 5G-VANET enabled solutions. This chapter presents a survey of clustering approaches in the VANET research area. The survey provides a general classification of the clustering algorithms, presents some of the most advanced and latest algorithms in VANETs, and it is among the fewest works in the literature that reviews the performance assessment of clustering algorithms.
Metadata
Item Type: | Book Section |
---|---|
Refereed: | Yes |
Subjects: | Computer Science > Algorithms Engineering > Telecommunication |
DCU Faculties and Centres: | DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing DCU Faculties and Schools > Faculty of Engineering and Computing > School of Electronic Engineering |
Publisher: | IGI Global |
Official URL: | https://dx.doi.org/10.4018/978-1-7998-7708-0.ch042 |
Copyright Information: | © 2021 IGI |
Use License: | This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License |
ID Code: | 27077 |
Deposited On: | 27 Apr 2022 10:25 by Gabriel Muntean . Last Modified 19 Sep 2023 08:56 |
Documents
Full text available as:
Preview |
PDF
- Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
430kB |
Downloads
Downloads
Downloads per month over past year
Archive Staff Only: edit this record