In recent times, the research community has demonstrated significant interest in Underwater Wireless Sensor Networks (UWSNs), where extensive sensor deployments in oceans and rivers aim to monitor the underwater environment. Energy consumption poses a primary challenge due to the difficulty of replacing or recharging batteries in these environments. Existing studies have employed K-Means technology to minimize power consumption in underwater transmission nodes. However, these studies have often overlooked the consideration of residual energy and void region creation in their optimization approaches. To address these challenges, we introduce a novel Hybrid path finder-based vortex search (HPF-VS) algorithm, utilized for cluster head selection and optimization of node locations and remaining energy. To extend network coverage beyond limited transmission ranges, inaccessible nodes at the network periphery employ the improved Dwarf Mongoose Optimization (IDMO) algorithm. Our proposed techniques demonstrate superior performance compared to existing methods, showcasing minimized energy consumption, reduced delay, improved packet delivery ratio, and enhanced throughput. Specifically, the proposed approach achieves a delay of 2.01 s and a throughput of 32.21 Kbps, surpassing the performance of state-of-the-art methodologies we benchmarked against.
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