## 1 Introduction
Different from other studies, in our approach the systematic performance of UWSNs, including coverage, connectivity, durability and rapid-reactivity have been calculated. 1. We improve the normal body-centered cubic lattice (NBCL) [6] to cross body-centered cubic lattice (CBCL) for the deployment of UWSNs, and propose a Cross Deployment Networking Method (CDNM) for UWSNs suitable for the underwater environment. In the former NBCL, the body-centered cubic lattices structure is piled up layer by layer by regular ball-bodies. After improvement to the CBCL, the ball-bodies on the higher level are crossing stacked over the spaces between ball-bodies on the next layer, and the cubic space has been divided into hierarchies and monitored from top to bottom. Based on CBCL, a 3D UWSN deployment process and topology generation method are proposed. Then, based on CBCL and randomly deploy sensor nodes, a _K_-Connected _K_-Dominating Set (_K_-CDS) [7] is built as the virtual communication backbone, and a Cross Deployment Networking Method (CDNM) for UWSNs, suitable for the underwater environment, is further proposed. 2. A Systematic Quark-Performance Calculation Model (SQPCM) is proposed. Considering the requirements of ocean exploration and underwater monitoring missions, we analyze the relationships between systematic network performance and the influencing parameters from an integrated view, and divide the systematic performance of UWSNs into four items, including coverage, connectivity, durability and rapid-reactivity. At the same time, we summarize the influencing parameters impacting the systematic performance items into three categories: constraint parameters, device performance parameters and networking parameters. Furthermore, the measurement models of coverage, connectivity, durability and rapid-reactivity performance are established. Then the network performance is evaluated and calculated systematically. 3. In order to make UWSN have the adaptivity to adjust the network coverage, connectivity and effective run-time when the environment and mission change, a Networking Parameters Adjustment Method (NPAM) for optimized systematic performance of UWSNs is presented. The process of this method is composed of four parts, including state collection and detection, dynamic measurement model of an UWSN's performance, optimal adjustment model of the UWSN and optimal method based on genetic algorithm. Through this method, an optimal combination of networking parameters can be achieved. As a result, it is possible for the network to have the maximum systematic performance in different missions and environment. 4. Two simulation experiments have been carried out in this study, whose result demonstrates that the proposed approach is highly feasibility and efficient in UWSN networking and performance calculation. The goal of our work is to obtain a network with the best system performance by using the CDNM and SQPCM and using as few sensor nodes as possible. At the same time, the dynamic optimization adjusted in the network is realized by the NPAM. The rest of the paper is structured as follows: Section 2 describes related works. Section 3 shows the CBCL for the sensor nodes deployment and the CDNM of UWSN. The systematic performance items analysis and the SQPCM of an UWSN are shown in Section 4. Section 5 describes the NPAM for optimized systematic performance of UWSNs. The simulations showing the result of our proposal are presented in Section 6. Finally, Section 7 gives the conclusions.