Proposed energy efficient clustering and routing for wireless sensor network

Wireless sensor network (WSN) is considered a growing research field that includes numerous nodes used to gather, process, and broadcast information. Energy efficiency one of the challenging tasks in WSN. The clustering routing are capable approaches solve issues energy enhance network’s lifetime. In this research, multi-objective-energy based black widow optimization algorithm (M-EBWOA) proposed perform cluster-based over M-EBWOA-based optimal cluster head discovery assure an energy-aware main goal M-EBWOA minimize consumed by while improving data delivery performance analyzed as alive dead nodes, dissipated energy, packets sent base station, life expectancy. existing such low-energy adaptive hierarchy (LEACH), hybrid grey wolf optimizer-based sunflower (HGWSFO), genetic algorithm-particle swarm (GA-PSO), energy-centric multi-objective Salp Swarm (ECMOSSA) evaluate M-EBWOA. 100 for 2,500 rounds, which higher than LEACH, HGWSFO, GA-PSO, ECMOSSA.