## 7 Results and Discussion
Figure 4e illustrates the network throughput as the data rates and node density varied. There is an increase in NT with rising data rates and node density, despite a slight dip at 300 nodes. Higher data rates enable faster data transmission, allowing the network to process larger volumes of data in less time, thus improving the network throughput. Furthermore, as the node density increases, connectivity improves, which reduces the congestion and increases data flow. The slight dip at 300 nodes may result from temporary network congestion or increased collision due to suboptimal routing. However, as the node count reaches 400 and 500, the network recovers, benefiting from better connectivity and more efficient path selection that enhances the network throughput. Also, with the higher node density, the network can distribute the communication load more evenly. This reduces the burden on individual nodes and prevents congestion at a specific point, which leads to smoother data flow and improved network throughput. Figure 4f illustrates the sum of dead nodes as the data rates and node density varied. There is a significant reduction in the sum of DNs as the node density increases. At lower node density, fewer nodes are available to relay the data packets, which results in longer transmission distances and higher energy consumed per node, which leads to premature node death. As the node density increases, the average distance between nodes decreases, which allows more energy-efficient communication. Additionally, with the increase in the data rates, the number of DN reduces as faster data transmission reduces the time spent in transmission mode. This enhanced energy efficiency at higher data rates, particularly in less dense networks, further contributes to the observed reduction in dead nodes. Effect of Node Movement with Various Speeds: To examine the effect of node movement with different speeds on network performance, we carried out a series of simulations with fixed node movement speeds of static (fixed nodes), 1, 2, 3, and 4 m/s. The results from these simulations are illustrated in Figure 5 and explained in the paragraphs below. Figure 5a illustrates the end-to-end delay as the node movement (0 to 4 m/s) and node density varied. There is a significant decrease in end-to-end delay as the node density increases particularly in the range of 100 to 200 nodes with a gradual decline after this point. This reduction can be attributed to the higher availability of communication paths in denser networks, which shortens the average transmission distance between nodes, thereby dropping the sum of hops required to deliver the data packets to the destination. Given the relatively slow propagation speed of sound in underwater environments, shorter transmission distances significantly reduce propagation delay, hence improving the overall network performance. Furthermore, the impact of node movement speed on the routing stability becomes evident at higher speeds, particularly at 3 and 4 m/s, where frequent changes in topology lead to route discovery delays and link breakages, slightly increasing  
the end-to-end delay. In contrast, at lower movement speeds, particularly 0 m/s and 1 m/s, the network experiences fewer disruptions, resulting in more stable and reliable routing. Figure 5b illustrates the average energy utilization per node as the node movement (0 to 4 m/s) and node density varied. Although the AEC per node has decreased significantly,  
Figure 5: Impact of movement speed of the node on (**a**) end-to-end delay, (**b**) average energy consumption, (**c**) total energy consumption, (**d**) packet delivery ratio, (**e**) network throughput, and (**f**) dead nodes. the node movement has a relatively minor effect on the overall trend of the average energy utilization. As the node density rises, the network can maintain efficient routing, even with nodes moving at faster speeds.