Energy efficient clustering routing algorithm based on improved FCM

Abstract Wireless sensor networks (WSNs) play a crucial role in the Internet of Things (IoT). The sensor nodes (SNs) in WSNs are powered by batteries, making energy efficiency and network lifetime key issues in WSNs research. Cluster-routing algorithms are a focal point for addressing energy efficiency challenges. Selecting cluster heads (CHs) based on clustering algorithms can reduce the energy consumption of SNs and enhance overall network stability and sustainability. This paper introduces a method for selecting the number of clusters (\ (NC\) ) and CHs based on fuzzy clustering. The fuzzy C-means (FCM) clustering algorithm requires pre-setting the number of clusters, with no inclusion of CHs information in the output after running the algorithm. The number of clusters and selection of CHs were determined using the elbow rule and scoring criteria for CHs selection. The performance of the network under different monitoring areas is simulated and analyzed in this paper. Experiments demonstrate that the proposed algorithm outperforms existing algorithms in terms of network energy consumption and lifetime.