A Hybrid Delay Aware Clustered Routing Approach Using Aquila Optimizer and Firefly Algorithm in Internet of Things

Protocols for clustering and routing in the Internet of Things ecosystem should consider minimizing power consumption. Existing approaches to cluster-based issues environment often face challenge uneven This study created a method utilising swarm intelligence obtain more even distribution cluster heads. In this work, firefly optimization an aquila optimizer algorithm are devised select intermediate head nodes required accordance with NP-Hard nature clustered routing. The effectiveness hybrid approach has been evaluated concerning following metrics: remaining energy, mean distances, number hops, node balance. For assessing things platforms, metrics like network throughput living crucial, as these systems rely on battery-operated equipment regularly capture data transmit specimens base station. Proving effective, suggested technique found improve system energy usage by at least 18% increase packet delivery ratio 25%.