## 6 Thematic Taxonomy of UWSNs
### Architectural Elements
#### 6.1.2 Network Operation  
The objectives of network operation in underwater sensor networks are to manage and optimize various functions, characteristics, and performance criteria for appropriate applications. According to the recent articles published, we conclude that the trend of research and application development emphasizes more on localization and deployment tasks which has become the basis of underwater wireless network design to enhance overall network capabilities. Therefore, this section discusses the essential techniques and relevant features of each task to improve the network performance.  
Localization techniques have been widely explored in UWSNs and play a critical role for typical applications to provide information on the location of sensor nodes. In our review of published papers from 2013 to 2020, we categorized the localization algorithms into three main categories: stationary, mobile, and hybrid algorithms. The classification is subject to the movement of sensor nodes in UWSNs. Based on those categories, most of the researchers focused on localization techniques for stationary nodes.  
For the stationary localization algorithm, all sensor nodes are fixed and static in the specific region of interest either attached to surface buoys or anchored on the sea floor. A variety of techniques are available for determining the location of stationary nodes. A recent method in [23] proposed the use of standard ray equations to manage the existence of ambiguity in the anchor node position based on the rigidity theory. Ray-bending is the leading property for estimating accurate positions of the nodes in their simulation. Previously, ref. [24] emphasized that optimizing sensors can significantly improvethe performance of sensor localization techniques. The collected data is only essential if the position of the nodes is accurate. The authors applied a Cramer-Rao lower bound theory to obtain the optimal sensor position. Localization techniques also depend on packet transmission rates, especially for self-localization. For instance, ref. [25] proposed a method that aimed to reduce localization time with collision tolerance.  
Some applications particularly monitoring activities in the ocean require mobile sensors to move freely underwater in performing these monitoring tasks. The algorithm for mobile sensor localization is divided into centralized and distributed algorithms. In the centralized algorithm, the sink node acts as a center point to calculate the location of nodes; in the distributed algorithm technique, each node performs localization tasks individually. In any research studies or UWSNs applications that involve mobile nodes, energy consumption is a crucial aspect that must be considered, as mobile nodes require high energy to move, and it is difficult to recharge or replace battery power in real applications. Some recent studies have been conducted, including [26], which proposed to reduce energy consumption by decreasing communication overhead in the data transmission process. Alternatively, ref. [27] recommended self-localization with free time-synchronization based on ranging optimization. The researchers found that the uncertain speed of the sound would cause the distance estimation of the node localization to be less accurate.  
A hybrid localization algorithm is derived when both static and mobile nodes cooperate in executing a specific application. Typically, mobile nodes perform as data collector to gather data from static underwater sensor nodes. Instead of using only current location information in the estimation-based method, a prediction-based method computes node localization using both current and previous location information of sensor nodes.