Evaluating the suitability of the firefly algorithm for optimization in optical and IoT networks

Abstract The Internet of things (IoT) is a quickly developing field that is defined by networked smart devices that communicate with one another to carry out intelligent tasks. Because of the energy, latency, and bandwidth limits, these networks must be optimized efficiently. This study investigates whether the firefly algorithm (FA), a metaheuristic inspired by nature, is appropriate for optimizing crucial parameters in IoT networks. The paper provides a thorough examination of the algorithm’s routing ability, energy economy, and convergence. The FA’s advantages and disadvantages in several IoT settings are illustrated through comparative analyses with alternative optimization methods like PSO and GA. According to the findings, FA offers a favorable trade-off between computational cost and performance, which makes it appropriate for lightweight and flexible IoT optimization tasks.