Energy-Efficient Cluster-Based Reliable Routing Using Hybrid Nutcracker and Improved Sand Cat Optimization Algorithm for Extending Network Lifetime in WSNs

Abstract

In wireless sensor networks (WSNs), sensor nodes are deployed in a target region for sensing environmental physical parameters to attain the objective of reactive decision-making. These sensor nodes necessitate energy for processing and forwarding the sensed data to the base station (BS) for better data delivery in WSNs. Balanced energy utilization in WSNs prevents the problem of hotspot, and dynamic cluster head (CH) selection with reliable route establishment is a vital decision-making approach that helps in optimal path selection with maximized energy conservation. In this paper, a nutcracker and sand cat optimization algorithm (NCSCOA)–based multiobjective CH selection and sink node mobility scheme is propounded for enabling rapid and reliable data transmission with reduced energy consumption in heterogeneous WSNs. This NCSCOA handled the problem of hotspot as well as isolated nodes and facilitated loop-free routing with the support of the improved nutcracker optimization algorithm (INCOA) that makes the decision of routing using local and global search optimization processes. It constructed an energy-level matrix (ELM) by deriving the impactful factors of intercluster formation, distance between CH and BS, residual energy (RE), and node density for achieving optimal CH selection and route determination. In specific, improved sand cat optimization algorithm (ISCOA) is used during the intercluster formation phase by discovering the optimized path between source and destination during route establishment. Simulation-based findings of the proposed NCSCOA confirmed its efficacy by improving the mean number of alive nodes by 23.18%, reducing energy consumption and delay by 21.86% and 20.98% compared to benchmarked protocols.