# Cluster-Based Control Plane Messages Management in Software-Defined Flying Ad-Hoc Network
## 4 Evaluation
### Simulation Description and Metrics  
We consider the Mobile Multi-Media Wireless Sensor Network (M3 WSN) OMNeT++ framework [37] for our evaluation, which implements network stack for FANET communications as introduced in Section 3.1. We conducted 33 simulation runs with different randomly generated seeds, as it statistically provides a reliable behavior analysis of the proposal [38], and results show the values with a confidence interval of 95% [11; 12]. We set the simulation time as 300 seconds (s), and simulation parameters to allow wireless channel temporal variations, link asymmetry, and irregular radio ranges, as expected in a real FANET scenario [11]. The FANET is composed of 34 UAVs flying with speed raging between 5 and 10 m/s over the entire flat terrain of 200 \(\times\) 200 m [17] to explore and disseminate live video streaming from the environment. The FANET has one fixed Destination Node (\(DN\)) located at \((100,0)\), as expected in FANET multimedia applications, such as safety & security, environmental monitoring, and natural disaster recovery [9]. We consider one UAV located at \((100,100)\), working as controller node \(CN\) to periodically collect UAV information and send configuration commands [11].  
In terms of FANET operations, we scheduled a random event at a different location, where UAVs are monitoring and sending information from the environment. Based on the collected information, the controller node \(CN\) could detect an event (based on the event monitor module in the Global Manager) at a given location, and then establishes a route between source \(SN\) and destination \(DN\) nodes via multiple relay nodes \(RN_{i}\) based on UAV contextual information and the event location (based on the routing manager module in the Global Manager) [11]. For video application, we considered video sequences with different video features downloaded from the YUV video trace library and YouTube [39], where such videos are encoded using H.264 codec at 300 kbps, 30 fps, Group of Pictures (GoP) size of 20 frames, and common intermediate format (352 \(\times\) 288 pixels) [11].  
In the simulation, UAVs have a battery with an initial energy of 18'720 Joules [11] and are equipped with IEEE 802.11g with a nominal radio range \(R_{max}\) of 55 m [18; 40]. At the MAC layer, we consider the CSMA/CA MAC protocol without using RTS/CTS messages and retransmissions. At the application layer, we consider the QoE-aware redundancy mechanism to add redundant packets only to priority frames [17]. We have conducted simulations with three different control plane message management mechanisms, namely SDN-FANET, SDN-FANET + PREDICTION, and CAPONE. Particularly, SDN-FANET considers the SDN paradigm applied to FANET, which considers a flat network architecture with periodic transmissions of global UAV contextual information. On the other hand, SDN-FANET + PREDICTION also considers a flat network architecture with the control message dissemination operations introduced in Section 4.2. Finally, CAPONE improve the control messages transmission performance by predicting the positions of the UAVs, and considers hierarchical network architecture, as introduced in Section 3. For all proposals, we are evaluating the PDR, position prediction error, overhead, and remaining energy.  
* PDR (%): The ratio between the number of control messages sent by UAVs and the number of delivered control messages at the controller node \(CN\).
* Position prediction error (meters): Error between the UAV position at the controller node \(CN\) and the current UAV position at each time interval.
* Overhead: Total number of control messages \(msg_{CI}\) transmitted with UAV contextual information during the entire simulation.
* Remaining energy (%): The ratio between the current energy level and the initial energy level by each UAV.