Multi-Objective Energy Efficient Adaptive Whale Optimization Based Routing for Wireless Sensor Network

In Wireless Sensor Networks (WSNs), routing algorithms can provide energy efficiency. However, due to unbalanced consumption for all nodes, the network lifetime is still prone degradation. Hence, efficient was developed in this article by selecting cluster heads (CH) with help of adaptive whale optimization (AWOA) which used reduce time-consumption delays. The multi-objective function CH selection. clusters were then created using distance function. After establishing groupings, supercluster head (SCH) selected benefit a fuzzy inference system (FIS) collect data CHs and send them base station (BS). Finally, data-transfer procedure, hop count used. An Oppositional-based Whale algorithm (OWOA) multi-constrained QoS AWOA. performance proposed OWOA methodology analyzed according following metrics: delay, delivery ratio, energy, NLT, throughput compared conventional techniques such as particle swarm optimization, genetic algorithm, algorithm.