Clustering based on Hybridization of Genetic Algorithm and Improved K-Means (GA-IKM) in an IoT Network
Year: 2024
Type: article
Abstract: 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 OKmeans algorithms. Simulation results show that the proposed algorithm performs well in terms of network lifetime and energy consumption.
Authors: Moez Elarfaoui, Nadia Ben Azzouna
Institution: Tunis University
Language: English
Subfield: Computer Networks and Communications
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4406463448