Abstract
Underwater robots, also known as autonomous underwater vehicles (AUVs), are amazing machines that are becoming increasingly important in a variety of disciplines, including sea environment exploration, data collection (for climate change), industry, and the military. Wireless nodes and relay nodes are randomly distributed and incorrectly selected, leading to void holes. Autonomous Underwater Vehicles (AUVs) for the UWSN were explored as a solution to the problem of void holes. The selection of an energy-efficient routing path that reduces the number of void holes has been presented using a neuro-fuzzy-based cluster-head selection and a k-means-based cluster creation. The creation of energy-efficient clusters is ensured by dynamic scheduling, which is also utilized to save energy. This protocol can deal with node failures in packet transmission in a timely way because of multi-hop routing. Simulated network performance is evaluated using the NS3 (AquaSim module) simulator, which includes the performance metrics such as average energy consumption, latency and packet delivery rate as well as throughput.
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