Informations générales
Grade
Doctorant
Biographie courte
PhD supervisor : Nadia Ben Azzouna | SMARTLab
Holder of a computer engineering degree obtained in 2001 from ENSI (Tunisia). Computer technologist at the Higher Institute of Technological Studies of Zaghouan and member of the SMART Laboratory (Tunisia) since 2022. His current research focuses on energy optimization in the Internet of Things (IoT).
Axes de recherche
Publications
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2024Moez Elarfaoui, Nadia Ben Azzouna
CLUSTERING BASED ON HYBRIDIZATION OF GENETIC ALGORITHM AND IMPROVED K-MEANS (GA-IKM) IN AN IOT NETWORK
International Journal of Wireless & Mobile Networks (IJWMN), Vol.16, No.6, December 2024, 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.
BibTeX
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- Marutho, Dhendra, Sunarna Hendra Handaka, and Ekaprana Wijaya. « The determination of cluster number at k-mean using elbow method and purity evaluation on headline news. » 2018 international seminar on application for technology of information and communication. IEEE, 2018.
- Kodinariya, Trupti M., and Prashant R. Makwana. « Review on determining number of Cluster in K-Means Clustering. » International Journal 1.6 (2013): 90-95.
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- DEL-VALLE-SOTO, Carolina, RODRÍGUEZ, Alma, et ASCENCIO-PIÑA, Cesar Rodolfo. A survey of energy-efficient clustering routing protocols for wireless sensor networks based on metaheuristic approaches. Artificial Intelligence Review, 2023, p. 1-72.
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