# FANET Routing Protocol Analysis for Multi-UAV-Based Reconnaissance Mobility Models
## 1 Introduction  
An ad hoc network is a wireless network of mobile nodes without using an existing network infrastructure. A flying ad hoc network (FANET) is an ad hoc network with aircraft as nodes. FANETs can be used for communication between unmanned aerial vehicles (UAVs) and a ground control station (GCS). The types of FANET can be classified according to the types of aircraft (e.g., rotary wing and fixed wing), because the speed of aircraft is different, which affects the topology of nodes in the network. The faster the nodes, the faster the network topology changes. The more nodes, the higher the density of the FANET is. For example, when the density of nodes is low, nodes frequently join and leave the network. Furthermore, the network topology changes regularly or irregularly according to mobility models. All of these characteristics of FANETs affect the performance of communication between UAVs and GCS. When it comes to the FANET routing protocols, it is the most important to effectively maintain the FANET network topology in order to transmit packets from UAVs to GCS or vice versa. However, many factors, such as the density, mobility, speed of flight nodes, and GCS location, can affect the performance of FANET routing protocols. Therefore, there is no particular routing protocol that can be considered superior to others in all of FANETapplications. Therefore, an appropriate routing protocol should be identified according to the scenarios and environments to which the FANET is applied. Many studies have analyzed FANET routing protocols. However, as far as we know, most of the studies did not consider the scenarios and environments to which the FANET is applied. Many studies did not mention the mobility model, or used only simple mobility models such as random waypoints [1; 2; 3; 4; 5; 6; 7; 8; 9; 10; 11; 12; 13; 14; 15; 16; 17]. Three studies used two and four mobility models [18; 19; 20], but the studies did not consider specific FANET scenarios. The most similar works to ours are two studies that analyzed FANET routing protocols based on specific scenarios [21; 22]. However, the study in [22] assumed different scenarios from ours. Only one study in [21] assumed a reconnaissance scenario like ours, but their experiment is based on a very particular circumstance that all of the nodes are connected to a satellite system, which differs from ours. We assume the reconnaissance scenario, where UAVs should evenly reconnoiter the reconnaissance area. Meanwhile, the moving patterns of UAVs should be irregular so that the enemy must not be able to predict the movement of UAVs. With our assumed scenario, we analyze and evaluate three routing protocols (AODV, DSDV, and OLSR) with five mobility models (SRWP, RDPZ, DPR, EGM, and MP). It helps identify routing protocols and mobility models suitable for reconnaissance scenarios. We also evaluate combinations of routing protocols and mobility models under various conditions, such as the number, connectivity, and speed of nodes, and GCS location, so as to understand how the factors can affect the performance of transmitting packets from UAVs to GCS. As a result, AODV showed the highest PDR performance in multiple UAV-based reconnaissance scenarios. In the combination of routing protocols and the mobility models, SRWP showed the highest PDR performance with AODV. RDPZ and EGM also showed reasonable performance under the consideration of the reconnaissance rate. We also observe interesting facts, as follows. First, even if network connectivity (i.e., density) increases, the performance of a routing protocol does not improve, rather degrades after at some point. Second, the GCS location affects the PDR performance of the combination of a routing protocol and a mobility model. Our contributions are as follows. First, we defined a multi-UAV-based reconnaissance scenario to analyze routing protocols with mobility models.