## 4 Simulations
### Evaluation of EDETA-e Protocol Underwater
#### 4.1.2 Simulation Results  
Table 1 shows the difference in network lifetime for each scenario. A confidence interval in which the specified average values will reside is given with a confidence level of \(95\%\). The average value ofthe network lifetime for each scenario is fairly stable, varying at most between \(\pm 1.01\%\). Also a decrease of the network lifetime can be observed with the increase of the deployment's area, although we believe that this decrease is more strongly related to the existing node density. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Meters** & \multicolumn{2}{c}{**100 \(\times\) 100**} & \multicolumn{2}{c}{**150 \(\times\) 150**} & \multicolumn{2}{c}{**200 \(\times\) 200**} \\ \hline Nodes & 100 & 200 & 100 & 200 & 100 & 200 \\ Average & 702,400 s & 704,000 s & 693,250 s & 689,450 s & 700,550 s & 693,900 s \\ Confidence interval & \(\pm\)0.78\% & \(\pm\)0.36\% & \(\pm\)0.45\% & \(\pm\)0.53\% & \(\pm\)1.01\% & \(\pm\)0.28\% \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Network alive time. Figure 3: Alive nodes _vs._ time with 100 nodes and 200 nodes. (**a**) 100 nodes scenarios; (**b**) 200 nodes scenarios. This can be better observed in Figure 3, where a plot of alive nodes over time for the six different scenarios is illustrated. Figure 3(a) depicts these values for the 100 nodes scenarios showing no significant differences between them. Figure 3(b) shows the evolution of the alive nodes over time for the 200 nodes scenarios and it provides more interesting data to analyse. Although the simulation end time for the three different deployment areas is almost the same, the evolution of the alive nodes over time is different. It can be seen that, at the \(100\times 100\)\(m^{2}\) deployment area, there are some nodes that deplete their energy almost at the beginning of the simulation and as we increase the scenario area the nodes start to die later. This behaviour is explained by the node density. When node density is high in the deployment area, some nodes will remain awake longer at the configuration phase. This leads to higher energy consumption. Hence, these nodes will die sooner than expected. The optimum node density will vary in respect to the transmission range. Further studies have to be conducted in order to give more insights in the effect of this parameter. Furthermore, the increase of the transmission range will lead to higher propagation delays and will likely increase the collision probability during the  
Figure 4 depicts the accumulated spent energy by all nodes over time for the first 40,000 s. Figure 4(a) shows this spent energy for the 100 nodes scenarios. As expected from Figure 3(a) there are no big differences between scenarios. There is one big slope, however, from the beginning of the simulation to 4,000 s. Here the energy consumption increases quite fast. This part corresponds to the first sub-phase of the initialization phase where normal nodes are trying to join a CH, so there is high activity in the network. After this first sub-phase is done and the nodes have joined their cluster, only the CHs will remain awake building the tree schedule to send their data to the sink. So, there is really low energy consumption until the end of the initialization phase. After the initialization phase, the normal operation phase begins. In this scenarios, it corresponds to the period beginning at 18,000 s until the end of the simulation. In Figure 4(b) the same analysis was done for the 200 nodes scenarios. It depicts differences in the accumulated energy spent by the nodes depending on the area of the scenario, corroborating the results presented by Figure 3(b). As it can be seen, the increase in energy consumption is given in the initialization phase and after that, during the normal operation phase, the slope is the same for all the given scenarios. This indicates that the node density is a determining factor at the initialization phase but after that, it does not have a big influence.