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APSO-MVS: an adaptive particle swarm optimization incorporating multiple velocity strategies for optimal leader selection in hybrid MANETs.

Authors :
Priya, J. Sathya
Femina, M. A.
Samuel, R. A.
Source :
Soft Computing - A Fusion of Foundations, Methodologies & Applications; 2020, Vol. 24 Issue 24, p18349-18365, 17p
Publication Year :
2020

Abstract

In this paper, we propose a hierarchical topological-based auto-configuration scheme for MANETs providing global internet connectivity among leader and member nodes to reduce the control overhead. The proposed scheme has performed the duplication address detection (DAD) operation through selecting a pre-configured node called coordinator node by a new joining cluster node. Hence, the overhead is reduced by the elimination of DAD messages broadcasting in the whole network. Also, the clustering problem in MANETs is solved by introducing a new adaptive particle swarm optimization with multiple velocity strategy (APSO-MVS) algorithm for a new leader selection with the frequent departure and failure of a leader node. However, to enhance the robustness and global searching ability of classical PSO, the three new velocity updating strategies are used in a newly developed APSO-MVS algorithm. This proposed APSO-MVS algorithm has considered multiple node metrics (node distance from the cluster group centre, node speed and node density) for the selection of an optimal leader node. Simulation results have proved the efficacy of proposed protocol in overhead reduction compared to other existing auto-configuration protocols and in terms of 15 benchmark test functions. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
14327643
Volume :
24
Issue :
24
Database :
Complementary Index
Journal :
Soft Computing - A Fusion of Foundations, Methodologies & Applications
Publication Type :
Academic Journal
Accession number :
147104433
Full Text :
https://doi.org/10.1007/s00500-020-05034-z