2025/11/10 by Alsharfa, Raya Majid, Feghhi, Mahmood Mohassel, Majeed, Majid Hameed
Computer Science · #Distributed #Energy Efficient Wireless Sensor Networks #FOS: Computer and information sciences #FOS: Electrical engineering #FOS: Mathematics #Internet of Things and AI #IoT and Edge/Fog Computing #Optimization and Control (math.OC) #Parallel #Signal Processing (eess.SP) #and Cluster Computing (cs.DC) #electronic engineering #information engineering
paper · doi:10.48550/arxiv.2511.06735
openalex publication_date 2025/11/10 · openalex created_date 2025/11/12 · openalex updated_date 2026/07/28
Wireless sensor networks (WSNs) face critical challenges in energy management and network lifetime optimization due to limited battery resources and communication overhead. This study introduces a novel hybrid clustering protocol that integrates the Water Strider Algorithm (WSA) with Fuzzy C-Means (FCM) clustering to achieve superior energy efficiency and network longevity. The proposed WSA-FCM method employs WSA for global optimization of cluster-head positions and FCM for refined node membership assignment with fuzzy boundaries. Through extensive experimentation across networks of 200-800 nodes with 10 independent simulation runs, the method demonstrates significant improvements: First Node Death (FND) delayed by 16.1% (678±12 vs 584±18 rounds), Last Node Death (LND) extended by 11.9% (1,262±8 vs 1,128±11 rounds), and 37.4% higher residual energy retention (5.47±0.09 vs 3.98±0.11 J) compared to state-of-the-art hybrid methods. Intra-cluster distances are reduced by 19.4% with statistical significance (p < 0.001). Theoretical analysis proves convergence guarantees and complexity bounds of O(n× c× T), while empirical scalability analysis demonstrates near-linear scaling behaviour. The method outperforms recent hybrid approaches including MOALO-FCM, MSSO-MST, Fuzzy+HHO, and GWO-FCM across all performance metrics with rigorous statistical validation.