Fuzzy logic–enhanced LEACH protocol for scalable wireless sensor networks

Abstrak

This study aims to enhance the LEACH protocol by mitigating its intrinsic stochasticity through the use of fuzzy c-means (FCM) clustering. This approach enables the design of WSN protocols with improved energy efficiency, stability, and scalability. To this end, two fuzzy logic–based protocols are proposed: CFFC-LEACH for small-scale deployments and VGFC-LEACH for large-scale environments. CFFC-LEACH employs artificial intelligence to generate optimal clusters by determining the appropriate number of clusters and efficiently partitioning the sensing area. VGFC-LEACH addresses wide-area monitoring challenges by dividing the network field into virtual zones of 100 x 100 m² to reduce communication distances. Within each zone, a leader is selected in every round based on residual energy and distance to the base station (BS). Clustering is performed using FCM, while cluster heads (CH) are selected through an objective function. Compared to LEACH and EDK-LEACH, network lifetime (NL) is extended by 61.26% and 46.59% with CFFC-LEACH, and by 245.81% and 657.44% with VGFC-LEACH, respectively. Which demonstrate that the proposed protocols significantly outperform LEACH and EDK-LEACH.