Internet of Things Energy Efficient Cluster-Based Routing Using Hybrid Particle Swarm Optimization for Wireless Sensor Network

Specialized transducers in wireless sensor networks that ofer sensing services to the inter- net of things devices have limited storage and energy resources. One of the most vital issues in WSN design is power usage, as it is nearly impossible to recharge or replace sen- sor nodes’ batteries. A prominent role in conserving power for energy-constrained net- works is served by the clustering algorithm. It is possible to reduce network energy usage and network lifespan prolongation by proper balancing of the network load with Cluster Head (CH) election. The single-hop inter-cluster routing technique, in which there is a direct transfer from CHs to the base station, is done by the low energy adaptive cluster- ing hierarchy. However, for networks with large-regions, this technique is not viable. An optimized Orphan-LEACH (O-LEACH) has been proposed in this work to facilitate the formation of a novel process of clustering, which can result in minimized usage of energy as well as enhanced network longevity. Sufcient energy is possessed by the orphan node,which will attempt to cover the network. The proposed work’s primary novel contribu-tion is the O-LEACH protocol that supplies the entire network’s coverage with the least number of orphaned nodes and has extremely high connectivity rates. A hybrid optimiza- tion utilizing simulated annealing with Lightning Search Algorithm (LSA) (SA-LSA), and particle swarm optimization with LSA (PSO-LSA) Algorithm is proposed. These proposed techniques efectively manage the CH election achieving optimal path routing and minimi- zation in energy usage, resulting in the enhanced lifespan of the WSN. The proposed tech- nique’s superior performance, when compared with other techniques, is confrmed from the outcomes of the experimentations.