Region Division Strategy for Multi-AUV Charging Scheme in Underwater Rechargeable Sensor Networks

With the limited battery energy, underwater rechargeable sensor networks (URSNs) has become a promising technology in ocean exploration and monitoring. Multiple autonomous underwater vehicles (AUVs) can be employed to charge the sensor nodes (SNs) in large-scale URSNs. However, few studies have focused on the issue of charging task of AUVs. This paper proposes region division strategy for multi-AUV charging underwater SNs, which aims to minimize the number of dead underwater SNs and maximize energy efficiency of AUVs. We first propose an improved K-means algorithm based on artificial fish swarm algorithm (IAFSA-KM) to divide the large scale networks into different regions. By dividing the URSN into regions, each AUV can be responsible for the charging tasks of the SNs in its corresponding region. Then we use IAFSA-KM algorithm to enhance the underwater optimal charging scheme. The experimental results show that the IAFSA-KM algorithm performs better in data classification tasks, and our charging scheme can reduce dead underwater SNs and promote the energy utilization of AUVs efficiently.