New Energy Efficient Clustering Method Based on Fuzzy Logic and Genetic Algorithm in IoT Network
Sirine Rabah, Aida Zaier, Hassen Dahman · 2020
Internet of Things (IoT) is an emergent smart technology which has a significant interest in the modern wireless communications field. Besides, the vast evolution of these networks, there are different issues. One of them is the source energy limited to the capacity of the sensor node's battery. Clustering in IoT network can improve the energy efficiency since that transmission energy is attached to the distance between transmitter and receiver. In this work, we proposed a new clustering approach for IoT network by using the Fuzzy Logic (FL) in IoT'node and the Genetic Algorithm (GA) in the Base Station. In our proposed method, first step includes the nomination process for being a cluster head (CH) and the second step includes the selection of the optimal among the qualified nodes as a CH for that particular cluster. Thus, the nomination method is based on the FL approach and selection CH method is based GA. Simulation results prove that the proposed method performs better than LEACH, PSO and GA protocols, reduces mainly energy consumption and enhances the network lifetime.