A Clustering Approach Based on Fuzzy C-Means in Wireless Sensor Networks for IoT Applications

Abstract

Sensor nodes in Wireless Sensor Network (WSN)-based Internet of Things (IoT) networks are often battery-powered, resulting in supplying relatively low energy. Energy efficiency in WSN-based IoT systems is a critical challenge as the IoT becomes more sophisticated owing to its widespread adoption. Clustering-based routing approaches are well-known approaches that have distinct benefits in terms of efficient communication, scalability, and network lifespan extension. In this research, we present a novel clustering technique for WSN-based IoT systems based on Fuzzy C-Means (FCM). To pick the best Cluster Head (CH), the method uses an FCM technique to build the clusters and a reduction in the total energy spent on each cluster. Rather than replacing CHs for dynamic clustering at each period in this study, we plan to use an energy threshold to hypothesize the dynamicity of CH dependent on existing energy levels, therefore increasing the sensor network lifespan.