Energy Efficient Cluster-Based Routing Protocol for WSN Using Nature Inspired Algorithm

WSN consist of tiny sensors that are distributed over the entire network and have the capability of sensing the data, processing it, and conveying it from one node to another. The purpose of the study is to minimize the power utilization per round and elevate the network lifespan. In the present case, nature-inspired mechanisms are used to minimize the power utilization of the network. In the proposed study, the Butterfly Optimization Algorithm (BOA) is used to choose the optimal quantity of cluster heads from the dense nodes (available nodes). The parameters to be considered for the choice of the cluster head are: the remaining power of the node; distance from the other nodes in the network; distance from the base station; node centrality; and node degree. The particle swarm optimization (PSO) is used to form the cluster head by choosing certain parameters, such as distance from the cluster head and the BS. The path is chosen by means of the Ant Colony Optimization (ACO) Mechanism. The route is optimized by the distance, node degree, and the chosen remaining power. The inclusive performance of the projected protocol is measured in terms of stability period, quantity of active nodes, data acknowledged by the base station, and overall power utilization of the network. The results of the put redirect methodology are correlated with the extant mechanisms such as LEACH, DEEC, DDEEC, and EDEEC (Khan et al. in World Appl Sci J, 2013; Arora and Singh in Soft Comput 23:715-734, 2019; Saini and Sharma in 2010 First international conference on parallel, distributed and grid computing (PDGC 2010), 2010; Elbhiri et al. in 2010 5th International symposium on I/V communications and mobile network, 2010) and correlated with the swarm mechanisms such as CRHS, BERA, FUCHAR, ALOC, CPSO, and FLION. This review will help investigators discover the applications in this arena.