A Dynamic Clustering Approach for Maximizing Scalability in Wireless Sensor Networks
Journal Title: Transactions on Machine Learning and Artificial Intelligence - Year 2017, Vol 5, Issue 4
Abstract
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 kmeans compared to LEACH (LowEnergy 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.
Authors and Affiliations
Hanane Kalkha, Hassan Satori, Khalid Satori
Keywords
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- EP ID EP310190
- DOI 10.14738/tmlai.54.3328
- Views 57
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