Optimized heuristic LEACH variants for energy-efficient routing in passive optical networks

Abstract To increase scalability and energy economy in Optical Wireless Sensor Networks (OWSNs), LEACH (Low Energy Adaptive Clustering Hierarchy) and its variants have been exhaustively investigated. Random LEACH selects cluster heads (CHs) probabilistically to maximize energy consumption; LEACH-C builds on this by selecting CHs dependent on residual energy, so greatly extending network lifetime. By means of further combination of dynamic clustering and load balancing, the proposed modified LEACH-C algorithm guarantees constant cluster sizes and efficient energy distribution. Based on simulation results, strong solutions for OWSNs: modified LEACH-C beats random LEACH-C in obtaining longer network lifetime (1,353 rounds) and higher communication efficiency. Computational complexity, communication overhead, load balancing difficulties, and scalability constraints are the challenges that need to be addressed. Node configurations and large-scale projects drawing attention to these challenges. If performance we want to increase performance and address these challenges, future directions demand the integration of hybrid energy models, adaptive reclustering systems, and machine learning for dynamic CH selection. Moreover quite essential for guaranteeing the resilience and adaptability of Modified LEACH-C in various WSN environments are security enhancements and practical testing.