## 2 Related Works  
With the increasing emphasis on effectively safeguarding national marine rights and interests, the upsurge in marine economic development and the significant progress in wireless sensor network technology, underwater sensor networks have become a new hot research area [1; 2]. They are deployed to perform collaborative missions such as ocean organism data collection, ocean monitoring, offshore exploration, disaster prevention, assisted navigation and navy military surveillance. However, since the underwater acoustic communication channel has limited bandwidth capacity, the unpredictable underwater environment, the unique characteristics of underwater acoustic channels, the complex deployment spaces and the difficulties arising in translating the state-of-the-art theoretical UWSN designs into their underwater equivalent, there are many problems on deep ocean exploration sensors, UWSN architecture, routing protocols and energy management, intricate network design and deployment, underwater communications and networking technology. Numerous works [1; 2; 8; 9; 10] show that node deployment, networking and performance evaluation on UWSN are challenging issues and must be solved promptly. Systematic performance analysis and calculation of UWSNs are becoming an important research topic. In [11], the coverage and connectivity issues for 3D UWSNs was investigated. Since node location can be random, redundant nodes have to be deployed to achieve 100% sensing coverage. Then a subset of the nodes can be dynamically chosen to remain active at a time to achieve sensing coverage based on their location at that time. One approach to achieve this goal in a distributed and scalable way is to partition the 3D network volume into virtual regions or cells, and to keep one node active in each cell. The results indicate that using cells created by truncated octahedral tessellation of 3D volume minimizes the number of active nodes. By adjusting the radius of each cell, this scheme can be used to achieve \(k\)-coverage [12]. The performance of these schemes for both 2D and 3D networks are analyzed and compared. When \(k=1\), \(k\)-coverage become 1-coverage. For 1-coverage, the 3D scheme is less efficient than the 2D scheme. The performance of 3D scheme improves significantly as compared to 2D scheme fork-coverage, for values of k is larger than 1. Sensor deployment, networking and systematic performance calculations of wireless sensor networks must be based on network routing protocols. [PERSON] et al presented in [13] an overview about the main issues in underwater wireless ad-hoc networks, and ad-hoc routing protocols were discussed. In [14] a routing algorithm named Prolong-SEP (P-SEP) is presented, and in [15] a new group-based underwater wireless sensor network was proposed. In [16; 17; 18], the authors built a model named Routing and Multicast Tree based Geocasting (RMTG) for geocast region holes in underwater sensor networks and provided detailed analysis and performance evaluation for the model. Many other researchers have analyzed performance features such as connectivity, reliability and energy efficiency when studying specifically the routing protocol, network architecture and topology control for UWSNs [19; 20; 21; 22]. Node deployment, networking and performance optimization are important research domains due to the changeable underwater environment, deployment at different depths, movement of nodes and so on. [PERSON] et al. pointed out in [23] that a sensor network has two competing objectives: (1) maximization of the network performance with respect to the probability of successful search for a specified upper bound on the probability of false alarms; (2) maximization of the network's operable life. Then they presented an adaptive energy management policy that will optimally allocate the available energy between sensing and communication at each sensor node to maximize the network performance subject to specified constraints. In [24], [PERSON] et al.