Improvised Ant Colony Routing Protocol via Q-Learning for Underwater Acoustic Environment

Due to their capacity to support underwater missions, the development of Underwater Acoustic Sensor Networks (UASNs) has drawn in considerable research interest in the last few years. With higher attenuation, longer propagation delay and bandwidth restrictions, acoustic communication channels in underwater are featured, which limits the communication between sensors and make the device intermittent. As a result, the main design issues for helping UASNs to precede the chores in severe underwater environments are energy usage and network lifespan. Therefore, this research work suggested an improvised routing protocol based on ant colony optimization that uses a reward mechanism (Q-learning) to acclimatize to the intricate underwater environment. The simulation results demonstrate the total energy utilisation, Packet Delivery Ratio (PDR), transmission delay and lifespan of the network, where the suggested approach outperforms the other standard routing protocols.