Power-Efficient Data Collection Scheme for AUV-Assisted Magnetic Induction and Acoustic Hybrid Internet of Underwater Things

Abstract

Power efficiency is a big concern in the Internet of Underwater Things (IoUT). The power consumption of underwater acoustic communications is typically in the scale of watts, which may drain the battery of underwater devices quickly. Whereas, the power consumption of underwater magnetic induction (MI) wireless communications is in the scale of milliwatt. Therefore, this article devotes to combine the underwater MI and acoustic communications to form a power-efficient underwater hybrid wireless network. Specifically, we investigate the power-efficient autonomous underwater vehicle (AUV) data collection schemes in an underwater MI and acoustic hybrid sensor network. We propose an alternating anchor nodes selection and flow routing (AANSFR) AUV data collection method, which alternately optimizes the AUV path planning and network data flow routing. The simulation results show that the proposed hybrid data collection scheme can significantly prolong the lifespan of underwater sensor networks.