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CLUSTERING BASED ON HYBRIDIZATION OF GENETIC ALGORITHM AND IMPROVED K-MEANS (GA-IKM) IN AN IOT NETWORK

Informations générales

Année de publication

2024

Type

Journal

Description

International Journal of Wireless & Mobile Networks (IJWMN), Vol.16, No.6, December 2024

Résumé

The continuous development of Internet infrastructures and the evolution of digital electronics, particularly Nano-computers, are making the Internet of Things (IoT) emergent. Despite the progress, these IoT objects suffer from a crucial problem which is their limited power supply. IoT objects are often deployed as an ad-hoc network. To minimize their consumption of electrical energy, clustering techniques are used. In this paper, a centralized clustering algorithm with single-hop routing based on a genetic algorithm and Improved k-means is proposed. The proposed approach is compared with the LEACH, K-means and OK-means algorithms. Simulation results show that the proposed algorithm performs well in terms of network lifetime and energy consumption.

DOI
DOI:10.5121/ijwmn.2024.16602
BibTeX
    
 	
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Auteurs

Moez Elarfaoui Moez Elarfaoui
Nadia Ben Azzouna Nadia Ben Azzouna

Axes de recherche

Optimization
Artificial Intelligence
Machine Learning