# Multilayered Network Model for Mobile Network Infrastructure Disruption
## 6 Simulations and Results
### Simulation Scenarios
#### 6.1.5 Results of Simulation Scenario 2  
The second simulation scenario adds UAV devices of DRONET layer to the WSN-MANET network, which complement the concept of MNM. This concept will be compared with the WSN network the same way as in the case of the first simulation scenario. In the case of the WSN-MANET-DRONET network, routing protocols use the same algorithm to find optimal paths like in scenario 1. To save energy in the DRONET layer, routing protocols deliver urgent data primarily using the MANET layer. Despite UAV accessibility, urgent data are transferred to DRONET layer only if the AP is not presented in a particular MANET subnet. The example of this scenario with the optimal routing path is depicted in Figure 21.  
The routing starts at the WSN layer, where the source WSN sensor finds the most optimal path in terms of the number of hops and data rate to the nearest WSN gateway sensor, which delivers the urgent data to the nearest MANET node. If functional AP is presented in the MANET subnet, the urgent data are transferred to this point. If the AP is not presented in the MANET subnet, the data are routed to the nearest available MANET gateway. Those MANET gateways are known because of the clustering algorithm performed by DRONET layer. After transferring the data to the DRONET network, the corresponding UAV selects the routing path according to OSLR routing protocol to the UAV, which is connected to the MANET subnet with functional AP. After the urgent data are transferred back to the new MANET subnet, the routing algorithm looks for the most optimal path to the AP. \begin{table}
\begin{tabular}{c c c c c} \hline \hline  & \multicolumn{2}{c}{**The Average Data Rates in 100 Kb Urgent Data Delivery [Mbps]**} \\ \hline  & \multicolumn{2}{c}{**WSN**} & \multicolumn{2}{c}{**WSN-MANET**} \\ \hline
**AP Position** & **Average** & **Standard Deviation** & **Average** & **Standard Deviation** \\ \hline Position 1 & 0.0264 & 0.0035 & 45.41 & 17.74 \\ Position 2 & 0.0276 & 0.0035 & 68.97 & 14.17 \\ Position 3 & 0.0275 & 0.0025 & 82.00 & 10.29 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: The average data rates in 100 Kb urgent data delivery from source WSN sensor to AP. The first result shows the total average delivery time of 100 Kb of urgent data from the source WSN sensor to the AP. However, in addition to WSN-MANET networks, these simulations also include DRONET networks. Therefore, it is possible to see a total of 3 delivery time components within AP Position 3 in the bar graph of WSN-MANET-DRONET network (Figure 22). In the case of Position 1 and 2, the DRONET network was not used due to the direct connectivity of the MANET network with the AP. The DRONET layer was used in simulation with the AP on Position 3 since AP is in the separate MANET subnet. Even the farthest AP was reached quickly in terms of delivery time, despite the use of three layers. WSN-MANET-DRONET network reduces the delivery time of urgent data on Position 1 by almost 70% compared to WSN layer. In the case of Position 2, this difference has already increased to about 79% and in the third position by 90%. The time component of the DRONET network is responsible for the significant decreasing of the delivery time at Position 3 due to the highest data rate on the routing path. At this data rate, the time component of transferring 100 Kb of urgent data is very small. Despite the higher number of hops and distance  
Figure 21: The example of optimal routing path in WSN-MANET-DRONET network. (**a**) Expample of optimal routing path through WSN and MANET layer. (**b**) Example of optimal routing path through WSN, MANET and DRONET layer. Figure 22: The total average delivery time of 100 Kb urgent data from the source sensor to the AP. between the source WSN sensor and AP, the DRONET layer was able to reduce the time of delivery that is comparable to the results on Position 1 and 2. The second result depicted in Figure 23 shows the average number of hops between the source WSN node and AP.