Clustering based on Hybridization of Genetic Algorithm and Improved K-Means (GA-IKM) in an IoT Network
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
- Nadia Ben Azzouna (ORCID: https://orcid.org/0000-0002-6953-2086)
- Moez Elarfaoui
Publication Details
- Journal
- International Journal of Wireless & Mobile Networks
- Published
- 2024-12-28
- DOI
- https://doi.org/10.5121/ijwmn.2024.16602
- Primary Topic
- Wireless Sensor Networks and IoT
- Type
- article
- Field-Weighted Citation Impact
- 0.00