A Hybrid Approach of Black Widow Optimization with Firefly (FF) Algorithm for Efficient Routing in Wireless Sensor Network

The sensor nodes that make up a Wireless Sensor Network (WSN) can be located anywhere and are linked wirelessly so that they can all keep tabs on the same set of physical characteristics in the area of interest. The nodes in a WSN run on internal batteries, thus when they run out of energy after repeated uses, the network has a shorter lifespan. Clustering and routing methods are frequently utilized in WSN to improve energy efficiency and network lifetime. For WSN’s cluster-based routing, this work introduces the innovative black widow optimization with firefly algorithm (FFA). The suggested BWO-FF algorithm comprises BWO based clustering procedure to elect an optimal set of cluster heads (CHs). The BWO algorithm creates a fitness function utilizing input parameters. In addition, route selection for inter-cluster communication requires an FF-based routing method. This routing method aims to enhance network throughput and lifetime by calculating the ideal route from each node to the sink in an effort to ensure uniform energy consumption across the network. MATLAB simulations have been used to analyze the proposed approach from several perspectives. The BWO-FF algorithm’s superiority to all other techniques studied is guaranteed by a selection of comparison evaluations.