Resource Scheduling in LoRaWAN using Chaotic Grouper-Moray Eel Optimization Algorithm

Long Range Wide Area Network (LoRaWAN) is employed in IoT applications because of its low power consumption and long-range communication capabilities. Still, efficient resource scheduling is a challenging aspect to enhance network performance and energy efficiency. This study introduces an optimal resource scheduling model for LoRaWAN using clustering and optimization techniques for handling large scale network applications. Initially, the Low-Energy Adaptive Clustering Hierarchy (LEACH) technique is employed to cluster the nodes for reducing energy consumption and improving communication efficiency. Then, the resource scheduling is employed using the proposed Chaotic Chebyshev Groupers-Moray Eel Optimization (ChGM) algorithm. The ChGM algorithm utilized chaotic mapping and evolutionary behaviors of groupers and moray eels to optimize scheduling decisions by considering the Packet Delivery Ratio (PDR) as the fitness criterion. The consideration of clustering with resource scheduling, the proposed model accomplished better PSR, PCR, Latency and Throughput of 97.848%, 3.209%, 15.474ms, and 97.842%in LoRaWAN-based IoT networks.