# Underwater Wireless Sensor Network Performance Analysis Using Diverse Routing Protocols
### Fisheye State Routing (FSR)  
Fisheye state routing, often known as FSR, is a routing technology for ad hoc networks that is multilayer and table-driven. It employs the scope technique. The goal is to reduce the amount of overhead that is associated with routing in extremely large, rapidly changing, and dynamic networks. According to its scope technique, the connection state changes are periodically broadcast at a defined frequency. The entirety of the network is divided into a variety of scopes, each of which is determined by the number of hops that are required to reach a specific node. The nodes that are deemed to be within this distance of one another are known as inner nodes, while the nodes that are further out are known as outer nodes. At a variety of different frequencies, neighbors obtain transmissions of the latest connection state updates. When communicating with more immediate neighbors, the information is transmitted at a lower frequency while simultaneously increasing its frequency. As a direct consequence of this, the nodes obtain connection state updates that are more accurate. It enhances the accuracy of the path over which packets are transmitted. As a consequence of this, FSR makes significant reductions in the connection overhead caused by the updating of routing tables. The ability of large mobile ad hoc networks to scale is improved as a result of this. It is suitable for rapidly changing topologies since it does not send any control signals when a link is severed. This makes it very flexible. The distance scope of the future fisheye state message exchange will not include the links that could not be established. In a mobile network that is dynamic, the links are kept fresh and free of loops by the use of regular table updates and sequence numbers [11]. Ad-hoc wireless networks, known as wireless sensor networks (WSNs), provide a wireless communication setup, such as underwater wireless communication [12]. Routing protocols for ad-hoc networks include AODV, DSR, DYMO, LAR1, Bellman-Ford, OLSR, Fisheye, STAR-ORA, ZRP, and STAR-LORA, among others [13]. The mobility model shows the movement of nodes and how their positions, speeds, and accelerations alter over time. When researching a new network protocol, it is crucial to simulate and assess its performance. The mobility model and the communicating traffic pattern are crucial in protocol simulation. Mobility models are used to describe user movement patterns. The traffic model describes the state of mobile services [14; 15; 16; 17; 18]. Figure 2 illustrates a realistic 3D underwater wireless communication scenario with various nodes. The potential challenges posed by the surrounding subsurface environment must be given the attention and consideration they require when considering underwater sensor networks [19; 20; 21]. The host conditions present numerous difficulties, including three-dimensional topology and continuous node movement. Additionally, many underwater applications, such as those used for detection or rescue missions, tend to be ad-hoc [22; 23; 24; 25; 26; 27]. As depicted in Figure 3, a WSN comprises spatially dispersed autonomous (self-organized) sensors that monitor environmental or physical conditions, such as temperature, sound, vibration, pressure, motion, or pollutants, and cooperatively transmit their data through the network to a central location. Modern networks are bi-directional, allowing for the control of sensor activity as well. Military usage of wireless sensor networks, such as battlefield surveillance, served as the impetus for their development. Today, these networks are employed in various commercial and consumer applications, including machine health monitoring, process control, and industrial process monitoring [28]. The WSN is composed of \"nodes\" ranging in number from a few to thousands and are each connected to one or more sensors.