Future of Information and Communication Conference (FICC) 2023
2-3 March 2023
Publication Links
IJACSA
Special Issues
Future of Information and Communication Conference (FICC)
Computing Conference
Intelligent Systems Conference (IntelliSys)
Future Technologies Conference (FTC)
Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.
Digital Object Identifier (DOI) : 10.14569/IJACSA.2018.090434
Article Published in International Journal of Advanced Computer Science and Applications(IJACSA), Volume 9 Issue 4, 2018.
Abstract: Vehicles in Vehicular Ad-hoc Networks (VANETs) are characterized by their high dynamic mobility (velocity). Changing in VANET topology is happened frequently which caused continuous network communication failures. Clustering is one of the solutions applied to reduce the VANET topology changes. Stable clusters are required and Indispensable to control, improve and analyze VANET. In this paper, we introduce a new analytical VANET's clustering approach. This approach aims to enhance the network stability. The new proposed grouping process in this study depends on the vehicles velocities mean and standard deviation. The principle of the normal (Gaussian) distribution is utilized and emerged with the relative velocity to propose two clustering levels. The staying duration of vehicles in a cluster is also calculated and used as an indication. The first level represents a very high stabile cluster. To form this cluster, only the vehicles having velocities within the range of mean ± standard deviation, collected in one cluster (i.e. only 68% of the vehicles allowed to compose this cluster). The cluster head is selected from the vehicles having velocities close to the average cluster velocity. The second level is to create a stable cluster by grouping about 95% of the vehicles. Only the vehicles having velocities within the range of mean ± 2 standard deviation are collected in one cluster. This type of clustering is less stable than the first one. The analytical analysis shows that the stability and the staying duration of vehicles in the first clustering approach are better than their values in the second clustering approach.
Mohammed Saad Talib, Aslinda Hassan, Burairah Hussin, Z.A. Abas, Zaniab Saad Talib and Zainab Sabah Rasoul, “A Novel Stable Clustering Approach based on Gaussian Distribution and Relative Velocity in VANETs” International Journal of Advanced Computer Science and Applications(IJACSA), 9(4), 2018. http://dx.doi.org/10.14569/IJACSA.2018.090434
@article{Talib2018,
title = {A Novel Stable Clustering Approach based on Gaussian Distribution and Relative Velocity in VANETs},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2018.090434},
url = {http://dx.doi.org/10.14569/IJACSA.2018.090434},
year = {2018},
publisher = {The Science and Information Organization},
volume = {9},
number = {4},
author = {Mohammed Saad Talib and Aslinda Hassan and Burairah Hussin and Z.A. Abas and Zaniab Saad Talib and Zainab Sabah Rasoul}
}