## 4 Results and Discussion
### Analysis of Results  
This section provides a comparative analysis of the proposed protocol with existing schemes. Energy consumption for DBR, MRP, and TM2 RP were measured in this section, and the results are shown in Figure 7. DBR did not employ an energy metric. It utilizes depth metric, which directly impacts the energy consumption that is consciously reduced, leading to consuming high energy. Moreover, MRP employs the residual energy and depth metric for selecting the next forwarding, which consumes less energy than DBR. Furthermore, the use of supernodes in MRP reduces the number of packet transmissions. In contrast, TM2 RP has more energy balancing compared to DBR and MRP. This is because the use of residual energy with a link quality metric in TM2 RP reduces the energy consumption between nodes considering the quality of the link, leading to choosing the forwarder node toward the distention efficiently. Therefore, TM2 RP accomplishes low energy consumption compared to MRP and DBR. \begin{table}
\begin{tabular}{c c} \hline
**Simulation Parameter** & **Value** \\ \hline Network topology & Random topology \\ Number of sensor nodes & 25–400 \\ Deployment area & 1250 m\({}^{3}\) \\ MAC protocol & 8.2.11 – DYNAV \\ Bandwidth & 10 Kbps \\ Area of transmission range & 250 m \\ Hello packet interval & 100 s \\ Communication medium & Acoustic Waves \\ Initial energy & 100 J \\ Power consumption & 2 w, 0.75 w, and 8 mw \\ Node movement & 0–3 m/s \\ Packet generation time & 15 s \\ Data packet size & 64 bytes \\ Number of Runs & 25 \\ \hline \end{tabular}
\end{table} 
Table 1: The underwater network simulation parameter sitting. The proposed protocol's total energy consumption is investigated in detail in Table 2, compared with existing techniques focusing on the respective average obtained values. It shows that the average energy consumption values obtained by TM2 RP were 30% and 55% for MRP and DBR, respectively. Based on the percentage above, the proposed algorithm provides more stability compared with the literature. TM2 PR employed underwater characteristics resulting in high energy-saving performance. This result is further shown clearly in Figure 8, where energy consumption observations and percentage gain are demonstrated in close relation for better clarity. The results provided in Table 3 and Figure 8 are thus confirmed. Therefore, with significantly lower energy consumption, the proposed protocol outperformed state-of-the-art algorithms. reducing packet loss, and resulting in the high delivery ratio in DBR compared to MRP with a smaller number of nodes. Moreover, MRP obtained less delivery ratio with less energy consumption than DBR because it provides energy balancing, but does not employ link quality metrics. In contrast, TM2 RP achieved the highest packet delivery ratio using less expensive methods. Therefore, the employment of retransmission techniques reduces the packet loss if the sensor has not been selected to transmit the data packets, which leads to an increased packet reception rate. Figure 8: The statistical outcomes of the comparative protocols with regard to energy consumption. Figure 9: Comparison of underwater packet delivery ratio with increasing number of nodes. We agree that link quality calculation is significant for the proposed framework. As much as link quality calculation or prediction will be better, the performance of the proposed framework is improved with regard to the packet delivery ratio. This is due to the average value consideration of LQI in Equation (4). Thus, the average value closeness to the actual value will impact the overall selection of underwater forwarding nodes resulting in a high packet delivery ratio compared to state-of-the-art techniques. Furthermore, TM2 RP utilizes the TM, which obtains more reliable and stable links, which reduces packet loss and results in a high delivery ratio toward the supernodes. A more detailed performance gain analysis is provided in Table 3 in terms of the packet delivery ratio of TM2 RP.