## 1 Introduction  
As sensor network research deepens and practical application needs are expanded, three-dimensional sensor networks have attracted increasing attention. In particular, the emergence of underwater network research in recent years has driven the development of three-dimensional sensor network systems [1; 2; 3]. In marine sensor node deployment, nodes are deployed in a three-dimensional underwater space to achieve the stereoscopic sensing of the monitored region. Figure 1 shows the structure of an underwater movable sensor network system [4; 5]. Sensor nodes that are equipped on autonomous underwater vehicles (AUVs) move to the monitoring sites that are required before utilizing their self-organization ability to carry out network formation and real-time monitoring in order to acquire various monitoring information within the network distribution region. After data integration and other forms of information processing, underwater acoustic communication is used to transmit real-time monitoring information to a sink node on the water surface before a sink on the water surface transmits the real-time information to observers. Because underwater nodes are often deployed in large areas of water that are sparsely populated by humans, the expensive batteries are not easily changed [6; 7; 8], and environmental damage causes frequent accidental node failures. Therefore, practical deployment algorithms must simultaneously consider coverage and connectivity [9; 10; 11; 12; 13]. Coverage requires every location in the monitoring region or every crucial location in the monitoring region to be monitored by at least one sensor node. Connectivity requires the network signal to not be segmented, i.e., it requires every deployed node to be connected \"many to one\" to the sink note. This is different from existing \"point-to-point\" communication networks (such as ad hoc networks). The research background of this study was based on regional point coverage, and the typical applications of these types of problems include environmental monitoring systems and target monitoring systems. In this type of application, a regional \"event\" that can partially represent environmental parameters is usually selected as the \"monitoring point\" for coverage (i.e., the node deployment for point coverage is actually completed). Monitoring the environmental parameters of these selected regional points enables a more accurate reflection of the environmental situation of the entire region. Therefore, the goal of the coverage design is to optimize the coverage of these selected monitoring points. In order to solve the coverage problems for target events in three-dimensional space, this study employs cubic modeling for underwater three-dimensional spaces. What is more, a coordinate system for a three-dimensional grid is used to represent the location of the nodes in order to propose an ant colony optimization-based self-deployment algorithm that maintains maximum coverage and connectivity. This algorithm was used to search for the optimal combinations in the network in order to achieve high network coverage and full connectivity (i.e., a connectivity rate of one). In contrast to conventional deployment protocols, our contribution mainly reflects the following two aspects:  
1. We convert the solution for the node locations into a combinatorial optimization problem for processing. This method establishes a heuristic search strategy for the network based on standard ant colony optimization algorithms in order to select valid nodes in candidate network nodes and to achieve full coverage of target events and connection between every node and the sink. 2. Taking into account the slow convergence speed and large search blindness of standard ant colony optimization algorithms, we also improve the path probability selection and pheromone updating mechanisms of a standard ant colony optimization algorithm in this study. Figure 1: Underwater mobile sensor network system structure.