## 5 Conclusions and Future Work  
In this paper, we proposed a triangle metric based multi-layered routing protocol for UWSNs, called (TM2 RP). The proposed algorithm is at a pressure routing algorithm that employs supernodes, link quality, and residual energy to choose the efficient next forwarding sensor among its candidate. Residual energy has a direct impact on balancing the total energy consumed by sensors. The link quality contributes to identifying the most reliable links between sender and receiver nodes that optimizes the delivery ratio toward the supernodes. Thus, TM2 RP combines these factors to calculate route cost. This route cost is then used to choose the next forwarding nodes. In the end, TM2 RP employs an overhead and retransmission mechanism to suppress redundant packet transmission and avoid packet loss.  
We evaluated the performance of TM2 RP using the NS2 Simulator with Aqua-Sim package for underwater along with a comparison against DBR and MRP. Based on the simulation results, TM2 RP achieved better results than DBR and MRP in terms of network lifetime, packet delivery ratio, energy consumption, and end-to-end delay. We suggest modifying the triangle metrics in future perspectives to combine more link quality metrics with improving stability and reliability links [23]. Moreover, the communication void in UWSNs and working in designing a void shows an awareness that TM2 RP  
Figure 14: The statistical outcomes of the comparative protocols with regard to end-to-end delay.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline  & **Node vs. End-to-End Delay (ms)** & \multicolumn{2}{c}{**\% Improvements of TM2 RP as Compared with Existing Techniques**} \\ \hline \hline
**Nodes** & **DBR** & **MRP** & **TM2 RP** & **\% Improvement of TM2 RP as Compared with MRP** & **\% Improvement of TM2 RP as Compared with DBR** \\ \hline
25 & 15.6721 & 12.962 & 7.0468 & 45.63 & 55.04 \\
50 & 21.7532 & 14.3984 & 9.1746 & 36.28 & 57.82 \\
100 & 43.1678 & 20.2798 & 11.706 & 44.92 & 74.12 \\
250 & 55.1045 & 32.0748 & 12.9658 & 59.58 & 76.47 \\
400 & 83.3475 & 45.4862 & 15.2354 & 66.51 & 81.72 \\ \hline \multicolumn{5}{c}{Average \% Improvements} & 50.58 & 69.03 \\ \hline \hline \end{tabular}
\end{table}
Table 5: The obtained results of TM2 RP with regard to end-to-end delay.  
needs further investigations [51]. Next, selecting the shortest path is another crucial issue that is taken into account for designing the shortest path TM2 RP [26; 52].  
Conceptualization, A.M.K.; Formal analysis, A.M.K.; Investigation, A.M.K.; Methodology, A.M.K.; Resources, H.Y.A. and L.A.; Supervision, O.K., J.L., and R.K.; Validation, M.A.S. and O.K.; Writing, A.M.K.; Review & Editing, O.K., M.A.A.-K., and M.M. All authors have read and agreed to the published version of the manuscript.  
Denship of Scientific Research (DSR), King Abdulaziz University, Jeddah (grant no. DF-524-156-1441).  
This project was funded by the Deanship of Scientific Research (DSR), King Abdulaziz University, Jeddah (under grant no. DF-524-156-1441). The authors, therefore, gratefully acknowledge DSR for the technical and financial support.  
The authors declare no conflict of interest.