Volume 16, Number 6

Clustering based on Hybridization of Genetic Algorithm and Improved K-Means (GA-IKM) in an IoT Network

  Authors

Moez Elarfaoui and Nadia Ben Azzouna, University of Tunis, Tunisia

  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 OK-means algorithms. Simulation results show that the proposed algorithm performs well in terms of network lifetime and energy consumption.

  Keywords

IoT - Network-BS - Clustering - CH - LEACH - Genetic algorithm - K-means - Optimization - Energy.