## 4 Simulation and Discussion
### Simulation Results  
The simulation results can be found from Figures 11-15. The simulation tool is DESER, which is an extension toolbox based on the NS-2 simulator. The simulation parameters can be found in Sections 3.1 and 4.1. In Figure 11, the average transmission power adjustment probability of the AUV is shown. From this figure we can find that this probability varies between 0.4 and 0.5. When the number of AUVs increases, there is no evidence showing that the transmission power adjustment probability increases too. This is because the probability is determined by the residual energy, the transmission power, the node degree, and the queue length jointly, so an increasing of the number of AUVs in the network cannot affect the probability greatly. \begin{table}
\begin{tabular}{c c} \hline \hline
**Parameters** & **Value** \\ \hline Simulation tool & DESERT 1  \\ Simulation area & 3000 m \(\times\) 3000 m \\ Number of AUVs & 3, 5, 7, 9, 11, 13 \\ Depth & 20 m \\ Water temperature (July) & 12 \({}^{\circ}\)C \\ Water salinity (July) & 18 g/L \\ Sound speed (July) & 1475 m/s \\ Initial transmission range & 1000 m \\ Transducer beam pattern & Horizontally Omni-directional \\ Data rate & 3 kbit/s \\ Bit error ratio & 10\({}^{-10}\) \\ Receive power & 1.3 W \\ Transmission power & 2.8 W \\ Channel model & Multi-path + Doppler spreading \\ Carrier & Sweep spread carrier (S2C) \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Simulation configuration. Figure 11: The average transmission power adjustment probability of PTC-FTC. Figure 14: The average node degree of PTC-FTC and FTC. Figure 12: The average transmission power adjustment ratio of PTC-FTC and FTC. Figure 13: The average residual energy of PTC-FTC and FTC. For instance, when the number of AUVs increases, the transmission power decreases and the residual energy increases, which can be found in Figure 13; however, due to the increase of the AUV's degree, the queue length will increase (shown in Figure 15); therefore, the probability may not increase. The transmission power adjustment ratio can be found in Figure 12.  
We can see in Figure 12 that the transmission power adjustment ratio of the PTC-FTC algorithm is much smaller than that of the FTC algorithm. The transmission power adjustment ratio in the FTC algorithm is about twice larger than that in the PTC-FTC algorithm. This demonstrates that the PTC algorithm is efficient at reducing the transmission power adjustment ratio. Similarly to the transmission power adjustment probability shown in Figure 11, the transmission power adjustment ratio does not increase with the increasing number of AUVs in the network. The reason is that when the number of AUVs in the network increases, the number of AUVs which need to adjust their transmission power increases too; moreover, according to the dynamics of an underwater cooperating AUVs network, there is no evidence that shows that the increase of the number of AUVs which need to adjust their transmission power is proportional to the increase of the total number of AUVs in the network. The notable properties of PTC-FTC algorithm also can be seen in Figures 13-15. In Figure 13, the residual energy of an AUV is presented. The residual energy in the PTC-FTC algorithm is larger than that in the FTC algorithm. With an increasing number of AUVs in the network, the residual energy increases when the number of AUVs in the network is smaller than nine and decreases when this number is larger than nine, both in the PTC-FTC algorithm and the FTC algorithm. This conclusion is easily understood.