Fuzzy Logic-Based Cluster Head Selection Method for Enhancing Wireless Sensor Network Lifetime.

Wireless Sensor Networks (WSNs) heavily depend on energy resources it crucial to enhance their longevity to achieve better performance. Clustering serves as an effective technique for controlling WSN topology. However, selecting an appropriate cluster head plays a critical role in the success of this approach. Cluster head selection involves considering various parameters, such as energy levels, node locations, and the number of neighbors, thereby rendering it a complex task. To address this complexity, we propose a cluster head selection method based on fuzzy logic, which emulates human decision-making by simultaneously handling multiple parameters. Our approach utilizes the Mamdani Inference engine and fuzzy parameters, including residual energy, node centrality, and distance from the base station. We evaluate our proposed method using heterogeneous networks featuring two and three levels of hierarchy. Through simulations, we demonstrate that our approach outperforms the SEP in a two-level network and the SEP-E protocol in a three-level network in terms of the network's lifetime. [ABSTRACT FROM AUTHOR]