Wolf Optimization-Based Energy-Efficient and Fault-Tolerant Protocols for Mission-Critical WSNs

Wireless Sensor Networks (WSNs), widely used in mission-critical applications, face persistent challenges in energy efficiency, fault tolerance, and real-time adaptability under dynamic, resource-constrained conditions. Addressing these limitations is essential for ensuring reliable and sustainable network performance in real-world environments. This study proposes and evaluates two specialized protocols to enhance energy-efficient clustering and fault-tolerant communication , thereby strengthening the robustness and extending the lifespan of WSNs. The first protocol focuses on energy-efficient clustering using a Wolf Optimization algorithm integrated with multi-hop routing, implemented within an Octave-based simulation framework. It features adaptive Cluster Head (CH) selection, dynamic hunt center updates, and layered communication visualization to optimize energy distribution and routing efficiency. The second protocol introduces a novel Fault-Tolerant Clustering Protocol (FTCP), which includes dynamic CH and Backup CH (BCH) selection, mobility-aware reconfiguration, and real-time rerouting. Simulations are conducted under heterogeneous energy levels, mobility patterns, and node failure scenarios, targeting real-world applications such as smart agriculture, military surveillance, and disaster response. Both proposed protocols demonstrate superior performance, achieving the highest node surviv-ability with 96 alive nodes and only 4 dead. Compared to TEEN and LEACH, they significantly extend network lifetime, enhance battery performance, and ensure balanced energy usage. Animation-based validation highlights FTCP’s robustness with stable CH/BCH distribution and rapid fault recovery.The results emphasize that integrating adaptive clustering with real-time rerouting is vital for building resilient, energy-efficient WSNs, with future advancements focusing on ML, Edge computing, and Cryptography for holistic next-generation solutions.