# Cluster-Based Control Plane Messages Management in Software-Defined Flying Ad-Hoc Network
## 3 Cluster-Based Control Message Management for FANET
### Network and System Model  
FANET can be used to monitor most kinds of environments without human intervention as it can reach hard areas, for instance, in disasters, emergency scenarios, buildings for structure inspection, and environmental surveillance [9]. In this sense, FANETs will be important in future smart city applications by enabling UAVs to collect measurements and to transmit for ground team or service, and thus UAVs will be the humans' eyes in the sky [6; 10]. It is because UAVs provide versatility,  
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flexibility, and relatively small operating expenses to support autonomous actions, where rescuers are unable to reach easily and quickly. Data captured from the event area enable humans (or even a service) in the control center to take appropriate action based on rich information to explore a hazardous area, where rescuers are unable to reach easily and quickly [11]. For instance, multimedia data plays an essential role in helping ground rescue teams to make appropriate decisions based on detailed visual information [29]. We considered an SDN architecture applied to FANET, such as introduced by [PERSON] et al. [12]. In this context, SDN-FANET infrastructure is divided into three distinct planes (application, control, and forwarding planes), where each plane can be programmed to meet particular application requirements [12]. The application plane supports different FANET applications, such as surveillance, searching, wildlife tracking, video services, and others. The forwarding plane considers (re)configurable nodes (i.e., UAVs) connected to a centralized controller. The control plane has a controller node responsible to perform all control functions, such as collision manager, routing, topology management, UAVs replacement, and others. Specifically, the controller could be a ground station or a regular UAV node to collect UAV information and send configuration commands periodically [11; 12]. We model the FANET as introduced by [PERSON] et al. [11]. The FANET is composed of \(n\) UAVs (nodes) with an unique identity (\(i\in[1,n]\)) monitoring an area of interest. We represent such UAVs considering a dynamic graph \(G(V,E)\). The vertices \(V=\{v_{1},\cdots,v_{n}\}\) represent a finite set of UAVs, and edges \(E=\{e_{1},\cdots,e_{n}\}\) means a finite set of asymmetric wireless links between 1-hop UAV (\(v_{i}\)) neighbors [11]. The subset of all 1-hop UAV neighbors inside the radio range \((RR)\) of a given UAV \(v_{i}\) is denoted by \(N(v_{i})\subset V\). We consider that each UAV \(v_{i}\) has a queue (\(Q\)) in order to buffer packets at the routing and MAC layers, which has a maximum queue capacity (\(Q_{max}\)). Packets are removed from the queue to be sent considering First In First Out (FIFO) algorithm. On the other hand, packets are dropped using the Drop Tail algorithm in case of buffer overflow. We consider UAV \(v_{i}\) equipped with a sensor unit to monitor the environment and a radio transceiver to send the collected data. For the convenience of notation, we denote Source Nodes (\(SN_{i}\subset V\)) as the subset of UAVs responsible for capturing data flows from the environment. The captured data is sent from the source nodes \(SN\) in a multi-hop fashion via multiple relay nodes (\(RN_{i}\subset V\)), i.e., as the subset of UAVs responsible to forwarding data from the source node to the destination node. We assume a FANET scenario composed of one static \(DN\in V\) equipped with a radio transceiver and unlimited energy, which is responsible for receiving the collected for further processing and dissemination. A UAV \(v_{i}\) can perform different tasks, so it can belong to different subset, however not at the same time. For instance, \(v_{i}\in SN\) infer that \(v_{i}\
otin RN\), and \(v_{i}\
otin DN\). Thus, \(RN\
eq SN\
eq DN\) during all the network life time. Each UAV \(v_{i}\) is aware of its own location \(L_{i,t}\) at a given timestamp \(t\) by means of a positioning system, e.g., GPS or Galileo.