# Underwater Wireless Sensor Networks Performance Comparison Utilizing Telnet and Superframe
## 4 Proposed Underwater Network Topology  
Existing networks are accessible with CBR as a deployment application. Telnet and Superframe applications are considered in the proposed network, and the settings for Telnet and Superframe applications are then compared. In the QualNet Simulator, the proposed scenario features a 1500-by-1500 square meter design with 250 nodes connecting the Telnet and Superframe programs, 75 of which are sensor devices, 25 are ship devices, and 150 are node devices. The simulation lasts a total of five hundred seconds. The node mobility model used is Random Waypoint Mobility, with a minimum speed of 1.5 m per second and a maximum speed of 2 to 11 m per second [23; 24]. LAR1, OLSR, Fisheye, STAR-LORA, and AODV are used as the first routing protocol. Figure 4 shows the internal link communication of CB-UWSN, where it has AUV: Autonomous Underwater Vehicle, BS: Base Station, CH: Cluster Head, SN: Sensor Node, and SS: Surface Station, with the communication links Microwave link, Acoustic link, and Optical link to establish the connection between the base station to the sensor nodes via the surface station. The graphs in the simulator were considered after the test was completed. Thus, the required performance metric, energy utilized in the transmit and receive modes, is obtained. Figures 5 and 6 show the proposed CB-UWSN underwater wireless communication scenario with multiple nodes in X-Y and 3D visualization for 250 nodes. Figures 7 and 8 show the runtime proposed scenario for CB-UWSN underwater wireless communication with various nodes in both X-Y and 3D visualization for 250 nodes. The purpose of Algorithm 1 is to cluster the sensor nodes in an underwater wireless sensor network based on their residual energy. The input to the algorithm is the number of sensor nodes k and the set of sensor nodes (n\({}_{1}\), n\({}_{2}\), n\({}_{3}\),..., n\({}_{\text{k}}\)). The output of the algorithm is the clustering of the sensor nodes. Figure 3: Communication model of UWSN. The algorithm consists of three steps:  
**Step 1:** Placement of k number of sensor nodes: this step involves placing the k sensor nodes in the underwater environment. **Step 2:** Find the energy between the sensor nodes: this step involves finding the energy between the sensor nodes by using the formula \(\mathrm{RE_{k}}=\mathrm{IE_{k}}-\mathrm{CE_{k}}\), where \(\mathrm{RE_{k}}\) is the residual energy of the kth node, \(\mathrm{IE_{k}}\) is the ideal energy of the kth node, and \(\mathrm{CE_{k}}\) is the consumed energy of the kth node. **Step 3:** Founded upon the high residual energy of the node is the cluster: This step involves clustering the sensor nodes based on their residual energy. The sensor node with high residual energy is selected as the cluster head, and the remaining nodes are assigned to the cluster head. Overall, the algorithm aims to form clusters of sensor nodes based on their residual energy, which can help in prolonging the network lifetime and improving the network performance. To simplify the process of building and evaluating the propagation model more easily, we assume that the 2 insulated magnetic dipoles are co-planar (=90 degrees) and parallel to the surface of the water. Furthermore, we assume that the propagation medium is homogeneous and isotropic. Despite the fact that dielectric phenomena can explain large signal losses at greater distances, and a lossy conducting medium can explain significant signal losses near the transmitter, we consider the theoretical foundation, which includes both the displacement current and the conduction current. If we assume that the received signal has a uniform distribution and acts like a plane wave, we may compute the average power density Equations (1)-(3). Figure 4: Internal link communication of CB-UWSN. Equations (1)-(3) describe the behavior of electromagnetic waves in an underwater environment.