# Adaptable and Automated Small UAV Deployments via Virtualization
## 4 Validation of the Solution
### Ad-Hoc network Routing Alternatives
#### 4.3.1 Scenario Definition  
To validate the usage of both protocols, we considered the simulation scenario depicted in Figure 6, highlighting that the included SUAV cloud platform represents a FANET. In this scenario, 16 SUAVs placed in a grid with a constant position with a separation of 70 m (maximum distance reached in the  
Figure 5: Validation measurements.  
simulation implementation with a reasonable link quality which covers an area bigger than 78,400 m\({}^{2}\)) compose the FANET with the aim of providing a network service during 1 h (3600 s). With respect to the SUAVs batteries, we assumed that those are mainly limited by flight energy consumption since other energy components demanded by the network services (e.g., AP, DCHP or Routing functionalities being executed by the SUAVs) are not comparable with the energy required by flight operations. For this simulation, we established a service time of around 20 min (1200 s time between failures) for each SUAV (battery lifetime) based on the technical specifications of the DJI Phantom 3 model [26]. In a second test, we reduced the time between failures to 5 min to get insight into the behavior of the selected protocols in extreme (unrealistic) conditions. Since battery life can be affected by different factors such as environmental conditions, maximum charge or flight conditions, we used a uniform distribution to model it characterized by the range [\(a=0,b=40\)], which provides an unfavorable dispersion of values with an average of 20 min. In a typical mission, when an SUAV battery is under a certain threshold, the SUAV will fly back to the GCS to replace it and another SUAV will come onto the scene to provide the service of the replaced SUAV. Normally, this replacement time is quite low since battery failures can be predicted from the GCS and the new SUAV can be sent to perform the replacement in advance. For that reason, we used an exponential distribution \(\lambda=1/3\), which gives an average replacement time of 3 s to model these low replacement times. Figure 7 shows an example of fail and replacement events for one of the performed simulations (note that the SUAV acting as AP and the one transmitting the telemetry information are not failing during the simulation since they are assumed to be statically positioned and the only power consumption is due to the network function provisioning).  
To perform the simulations on the wireless ad-hoc networks with different mobile nodes, we used Network Simulator 3 [42] (ns-3 provides a discrete-event network simulator for Internet systems). Specific existing modules for ns-3 are used to simulate the FANET protocols. Node movements have been calculated in advance in order to approximate them as much as possible to a real SUAV application. These individual movement traces are later installed on each node to perform the simulation. The network interfaces available in the different SUAVs are common IEEE 802.11b interfaces.  
Figure 6: FANET for simulation scenario.  
To measure the network performance, we set an Iperf flow between two edge nodes (UDP flow with a rate of 32 Kbps) emulating the telemetry information sent by one of the SUAV (denoted in Figure 6 as telemetry transmitter) that we have previously mentioned during the experimental validation in Section 4.2. All the simulation details can be found in Table 1.