FOC-MOP: Fuzzy Optimal Clustering Based Multi-Objective Parameter Route Selection for Energy Efficiency

Wireless sensor networks are emerging and involved in a wide range of applications. Improving energy efficiency is significant task WSNs. Energy consumption crucial problem that affects the network lifetime due to limitations nodes. So, it's required introduce more energy-efficient protocols for Different types solutions exist The optimized controlled if clustering an efficient data collection method. cluster heads aggregate from member nodes transmit aggregated BS (base station) either uncompressed or compressed manner after collecting all by cluster-heads (CHs). Due heavy inter-cluster relay aggregation Overhead, earlier death happens CHs located very close sink. There need reliable CH selection algorithms select prevent frequent reselection CHs. Therefore, this work, fuzzy optimal algorithm proposed improve network's lifetime. uses following multi-objective parameters: load, communication cost, neighbour density, inter intra-cluster distance, node selection. modified Emperor Penguin Optimization (EPO) used work determine route transmitting EPO helps multi-hop routing efficiency, reduces cost long-distance transmission, decreases utilization during transmission. considers parameters like link quality factor, relative distance residual factor technique was compared against methods Z-DSS, CCR, RETOPSIS, LEACH-FC. various packet delivery ratio, lifetime, consumption, end-to-end delay, Throughput studied. evaluation results prove mechanism achieves 40% with 60% lesser Overhead improves rate 50% than methods.