# High-Efficiency Clustering Routing Protocol in AUV-Assisted Underwater Sensor Networks
## 1 Introduction  
Currently, underwater sensor networks have become a crucial and challenging technology in scientific research and practical applications and have been widely used in acquiring underwater data and disaster warnings [1, 2, 3]. Nevertheless, owing to the special properties of underwater environments, such as high pressure, high salinity, temperature fluctuations, and current mobility, numerous challenges exist in the design and operation of underwater sensor networks, such as energy limitations, hydroacoustic signal attenuation, high transmission delays, and decreased reliability of data transmission [4, 5]. Apart from that, the energy of nodes is limited, and it is very complicated to replace batteries [6]. Therefore, reducing node energy consumption and improving network energy efficiency have become important issues in the development of underwater sensor network technology [7]. Traditional clustering protocols are effective in achieving energy efficiency in underwater sensor networks. LEACH [8] is a classical clustering protocol that organizes the network nodes into multiple clusters by rotating the cluster head nodes to reduce node energy consumption. Nevertheless, LEACH has several limitations when dealing with underwater sensor networks, such as the inability to adapt to the complicacy and variability of the underwater environment, and the random cluster head selection methodmay lead to an unbalanced load on some cluster head nodes, which accelerates energy consumption and leads to premature energy depletion at some nodes, thus affecting the network lifetime and reliability. In recent years, many scholars have conducted extensive research on clustering protocols for underwater sensor networks. [PERSON] et al. [9] introduced a Controlled-LEACH protocol (C-LEACH), which involves the deployment of a control node at the central position of the network topology; the control node handles operations such as cluster head selection and cluster formation, which greatly reduces the overhead of the sensor nodes in the network and effectively extends the network lifetime. Nevertheless, the processing time of the control node is longer, which increases the network latency. [PERSON] et al. [10] introduced an improved revised cluster routing algorithm named E-LEACH, which places nodes with higher residual energy as cluster head nodes. In the first round, all the nodes have equal chances of being selected as cluster head nodes; after the second round, the residual node energy starts changing, and the cluster head node is taken as the node with the highest residual energy. Compared to LEACH, this protocol improves selection, which saves energy and effectively extends the network lifetime but ignores the network connectivity problem. [PERSON] et al. [11] proposed an improved routing strategy named the EE-MDCHSRP, which dynamically selects the cluster head nodes by considering the node density, the residual node energy, and the minimum migration factor. This approach can effectively balance the cluster head node's energy and extend the network lifetime, but frequent cluster head election leads to considerable unnecessary energy consumption. [PERSON] et al. [12] proposed a new protocol named TCEB, which takes energy and path loss as influencing factors in selecting cluster heads and represents the topology control protocol as a noncooperative game, with a payoff function consisting of residual node energy and one-hop distance path loss, which can effectively distribute the energy consumption among all nodes. However, this protocol does not consider the mobility of sensor nodes. [PERSON] et al. [13] introduced a routing protocol called ECHERP, which focuses on balanced cluster head election. This protocol utilizes a balanced clustering approach and Gaussian elimination algorithm to choose a random node or a node with higher residual energy as a new cluster head at a specified time. The protocol also plans the number of cluster head cycles based on residual energy in order to prolong the network's lifetime.