Wireless Sensor Network (WSN) comprises a collection of sensor nodes deployed randomly in the sensing environment. Since energy efficiency remains a challenging design issue in WSN, clustering and routing techniques have emerged. The sensor nodes in WSN are restricted in energy, bandwidth and computation capabilities. In this research work, the WSN challenges, such as energy-constrained characteristics of the WSN sensor nodes, are focussed and can be resolved by using routing techniques. This paper presents an energy-efficient clustering with a modified monarch butterfly optimization-based multipath routing protocol (CL-BO-MRP) technique for WSN. The proposed model initially involves the cluster construction and Cluster Head (CH) selection process using Fuzzy Logic (FL). In addition, the Modified Monarchy Butterfly Optimization (MMBO) algorithm-based optimal route selection process determines the possible routes to a destination. The MMBO-based routing algorithm aims to reduce intra-cluster and inter-cluster communication costs. Applying fuzzy-based clustering and MMBO based routing helps achieve energy efficiency. An extensive simulation analysis is carried out to verify the adequate performance of the proposed models. The outcomes of the proposed models are examined under several aspects, such as Packet Delivery Ratio, Average delay analysis, Energy Consumption and Throughput. The detailed simulation outcome indicated the superiority of the proposed model CL-MMBO-MRP over the existing models under several aspects.

Clustering, routing, optimization, fuzzy, delay, energy consumption, fitness, monarch butterfly, Wireless Sensor Network, Networks.