Smart Cluster Head Selection Based on Residual Energy to Enhance Lifetime and Performance in WSN
Keywords:
Cluster Head (CH), Energy-aware Schemes, Lifetime, Network Degradation, Optimizing Energy, Performance Benchmarks, Residual Energy, Simulation Frameworks, Security-aware CH Election, Wireless Sensor Networks (WSNs).Abstract
Efficient cluster head (CH) selection is dominant to optimizing energy usage and prolonging the lifetime of Wireless Sensor Networks (WSNs). Traditional CH rotation approaches, such as LEACH, randomly elects CHs without considering nodes’ remaining energy, which often results in early network degradation. To mitigate this, energy-aware schemes have been proposed that incorporate residual energy as primary metric, offering substantial improvements in network longevity and data throughput. The CH selection based on residual energy is a well-established strategy to prolong the lifespan of WSNs and improve data delivery efficiency. This review synthesizes a variety of residual energy-based algorithms from simple LEACH modifications to advanced metaheuristic and fuzzy techniques highlighting their design principles, simulation-based results, practical challenges, and future research directions. This review synthesizes such advancements in CH selection, categorizing them into basic residual-energy threshold methods, multi-criteria/fuzzy decision-making techniques, and optimization-based metaheuristic strategies. We critically analyze algorithmic mechanisms, simulation frameworks, and performance benchmarks, and highlight trade-offs between computational overhead and energy gains.
Finally, we outline determined future research opportunities, such as distributed selection for scalable networks, real-world deployment validation, and security-aware CH election to foster resilient, energy-efficient WSN designs.
