## 6 Simulation Results
### Performance Trade-Offs  
In this section, we discuss the performance of our routing protocol in terms of achievements and drawbacks. The trade-offs of the selected existing protocols with our proposed scheme are listed in Table 3. The AURP lacks a residual energy threshold mechanism at the GN, which results in the unbalanced energy consumption mechanism. Figure 10a-c depicts the stability period and the existence of alive nodes in the network. The AURP achieves low end-to-end delay at the cost of high energy consumption. Moreover, extra burden on the intermediate nodes, due to the relaying of a huge amount of data, leads to the transmission loss increases at the end, as shown in Figure 15a-c. The AEERP has a mechanism to balance the energy consumption. However, the excessive association of the member nodes with the GN decreases its stability period, as shown in Figure 10a-c. The AEERP achieves reasonably high throughput (_cf._ Figure 13a-c) due to the introduction of the GN residual energy threshold mechanism, as compared to the AURP. Moreover, the AEERP achieves less end-to-end delay (_cf._ Figure 12a-c) at the cost of high energy consumption (_cf._ Figure 10a-c) as compared to the AEDG. In AEDG, the sub-optimized value of \(\beta\) for the elliptical path of the AUV is calculated through the Monte Carlo simulation method in order to increase the throughput with reduced energy consumption, as depicted in Figure 7a,b. Moreover, the sub-optimal assignment of MNs with their respective GNs balances the energy consumption with the residual energy threshold mechanism. The AEDG achieves high throughput (_cf._ Figure 13a-c) at the cost of high end-to-end delay (_cf._ Figure 12a-c). Moreover, it achieves a high stability period (_cf._ Figure 10a-c) and low transmission loss (_cf._ Figure 15a-c) due to the balanced energy consumption at the cost of high end-to-end delay (_cf._ Figure 12a-c). Note: If the GN is periodically rotated (time based) among the sensor nodes, then the energy is evenly consumed among nodes, such that pre-mature death among the nodes can be avoided; however, in consideration of the nodes' residual energy causing unnecessary energy waste when the network \begin{table}
\begin{tabular}{p{113.8 pt} p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline \hline
**Protocols** & **Mechanism** & **Advantages Achieved** & **Price Paid/at the Cost of** \\ \hline AURP & No mechanism to balanced energy consumption (Figure 10). & Less end-to-end delay (Figure 12). & Low stability period, high energy consumption and high transmission loss (Figure 10). \\ \hline AEERP & Mechanism to balance energy consumption (Figure 10) and no mechanism to limit the association of MNs with the GN. & Less end-to-end delay (Figure 12) and enhanced & High energy consumption and low stability period as compared to AEDG (Figure 10). \\ \hline AEDG & Sub-optimized elliptical path of the AUV and sub-optimal assignment of member nodes with the GN. & High stability period, low energy consumption (Figure 10), high network throughput (Figure 13) and low transmission loss (Figure 15). \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Performance trade-offs made by the routing protocols. becomes heterogeneous. On the other hand, if the GN is rotated on the basis of the residual energy, the then frequent GN rotation would consume surplus energy during the later simulation course. To better cope with this problem, the GN is rotated on the basis of the nodes' periodic residual energy (the hybrid approach of the time-driven and residual energy-driven approaches). Thus, the GNs are rotated at the cost of signalling message (overhead) exchange between the AUV and the nodes to be selected as the GNs. However, this overhead has no significant impact on the energy efficiency and throughput degradation, as compared to the achievements made due to the GNs' rotation. Since we have implemented periodic residual energy-based GN rotation, the GN rotation-based results do not show at the beginning an advantage compared to the non-rotating GN method (see Figures 10-15).