A Dynamic Clustering Approach for Maximizing Scalability in Wireless Sensor Networ
Hanane Kalkha, Hassan Satori, Khalid Satori · Transactions on Machine Learning and Artificial Intelligence · 2017
Scalability is an important and crucial issue which in routing protocols for Wireless Sensor Networks (WSNs). In this paper, we present an approach to achieving a balanced energy consumption rate using dynamic clustering to provide scalability in WSN. The proposed work in this paper is based on the dynamic clustering using k-means compared to LEACH (Low-Energy Adaptive Clustering Hierarchy), which is one of the most simple and effective clustering solutions widely deployed for WSN. The simulation results show that our proposed algorithm significantly improves high network scalability compared to LEACH.