## 2 State of the Art
### Real Experimental Studies  
In this subsection, we will see a compilation of papers that analyze, by means of real experimental studies, the performance of FANETs deployed by UAVs. Due to the high cost and complexity of building large-scale networks with variable topologies, and the difficulties related to the repetition of scenarios, it is challenging to find works that include real deployments of FANETs. The vast majority of the work completed expects the simulators used to be capable of simulating real conditions to ensure that the results they obtain or the algorithms they propose can resemble what could be obtained. However, we believe that a real deployment, controlling as many variables as possible and repeating the experiments several times, can provide greater assurance. The results obtained are, by comparison, more trustworthy. That is why we consider this work very interesting, helping the reader to understand the impact of choosing a routing protocol on the FANET performance.  
Analyzing works that focus on real FANET deployments, Rosati et al. [4] studied the performance offered by Predictive-OLSR (P-OLSR) and OLSR in a FANET composed of two small fixed-wing UAVs (called \"eBee\"). Their results showed that, because P-OLSR uses GPS information, the performance obtained both in simulation and in experimental tests improves that obtained with OLSR, reducing the number of communication interruptions.  
Furthermore, the P-OLSR performance was compared against OLSR and Babel in [5]. The results showed that P-OLSR, for the scenario they proposed (up to three UAVs with a highly dynamic ad hoc network), could provide more reliable multi-hop communication than Babel and OLSR.  
In [6], the authors compared two modes of operation of the 802.11 WiFi standard (access point and ad hoc using BATMAN-ADV) in a real experimental scenario in terms of coverage, throughput, and energy efficiency with up to two quadcopter UAVs. The results revealed a better performance of the access point mode in terms of received signal strength and throughput but worse performance in terms of power consumption than the ad hoc mode.  
The work presented by Lee et al. [7] proposed an approach similar to P-OLSR, in which the UAV nodes employed GPS information to improve the routing protocol, called Ground Control System-Routing (GCS-R). A real experiment was conducted with up to six UAVs in a network-coverage application scenario. The results showed that their proposed routing algorithm outperformed OLSR and DSDV in terms of throughput, stability, and network outage time. However, given that it suggests a centralized algorithm, it has a single point of failure that could be critical because of the instability of the UAV nodes and presents serious scalability problems.  
On the other hand, in [8], the authors showed the deployment of a FANET using BATMAN as the routing protocol, showing the capabilities that this type of network can offer in terms of coverage and throughput. They used a UAV in three different scenarios, and the results showed that the maximum distance they could transmit without packet loss was 117 m.  
Finally, the authors of [9] proposed a security protocol for FANETs called SUAP, which incorporates geographical leashes, hash chains, and public-key cryptography into the AODV routing protocol. Although SUAP proved to be effective in encrypting messages exchanged between nodes against various attacks, it did not provide a robust mechanism to recover from disconnections between nodes. According to the experimental result performed with three nodes, the delay to re-establish a new route when a node failure occurred was considerable, especially for real-time applications such as video capture, monitoring, and aerial photography. Moreover, its performance should be evaluated in a network with a high density of nodes. A summary of the reviewed papers can be seen in Table 1.