Enhancing Energy Efficiency in Wireless Sensor Networks with Optimized Cluster Head Selection Using Modified Cuckoo-Search Algorithm

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Dr. Sammulal Porika, Battini Sujatha




Stabilizing the energy of a wireless sensor network is regarded to be one of the primary concerns since it leads to increased lifespan of sensor nodes, which leads to a maximum network lifetime. Clustering and subsequent cluster head selection using new metaheuristic method are quite advantageous in this scenario. A new method for improving network lifespan while maintaining energy stability for sensor nodes is introduced in this study. This SACS-CHS plan has characteristics that are adaptable and aid in improved cluster head selection while leaving the used parameters unaltered. The fitness function assessed using the prior and current best solution incorporated the decreased population percentage notion. This CH selection is achieved by measuring residual energy, intra-cluster distance, and inter-cluster distance, and then calculating the fitness function to find the best CH candidates. The configuration also featured a gaussian sampling mechanism that allowed for exploitation and exploration to occur more often. In addition, Weibull has employed probability switching in the form of randomising trading exploration to allow the process to have a better mix of exploitation and exploration. Simulation findings indicated a 12.38% improvement in energy stability and a 14.21% increase in network lifespan, both of which are far greater than the baselines investigated for simulation.


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