Bio Inspired FFA Algorithm for Efficient Data Transfer in WSN

Wireless Sensor Networks (WSN) have emerged as a key technology with a wide range of possible applications. In routing methods that are specifically intended for wireless sensor network applications. An major routing challenge is determining how to raise the overall network's energy usage while avoiding the electricity that leads to hardware failures or dying; this state causes the network to run inefficiently and contributes to system mortality. In any system, improving routing performance is an essential. In this section, wireless communication that use an optimized bio-inspired algorithm called Firefly algorithm (FFA) to tackle routing challenges is investigated. FFA also stabilizes abided the level of energy focused by routing mechanism which is in multiple ways. Along with FFA, the concept of Q-Learning is used. Q-Learning is used to select the necessary FFA parameter for each agent. Finally, their performance was evaluated. Combining these two strategies increases accuracy and overcomes routing challenges in wireless communication, according to the experiments.