## 2 Materials and Methods
### Algorithms for DTNs with UAVs  
A DTN network is modeled with a graph. Graph nodes are of two types: fixed and mobile. There are no connections between the fixed nodes, so there is no possibility of data transmission, considering that the distance between the nearest two nodes is 4000 m. Network connections are provided by mobile nodes (UAVs), but their condition is not always the same; they have periods when they are active and periods when they are inactive. This means that there is not always an end-to-end path available between any two nodes in the graph. Five well-known routing algorithms for DTN networks (Epidemic, Spray and Wait, PRoPHET, MaxProp, and MaxDelivery [42]) and the new TD-UAV Dijkstra approach were tested on the triangle-shaped from Figure 5. Tests by choosing random sources and random destinations, which can be located on any node (marked as gray circle or grey rectangle), were performed. It was considered that the UAVs work every day from 7:00 AM to 6:00 PM. The messages can leave a source node between 7:00 AM. and 5:00 PM. A total of 1000 messages randomly sent in this interval of time were considered. Figure 4: Triangular-shaped flight mission profile of the UAV. Figure 3: Network cells: hexagonal cell with three UAVs. Epidemic is the basic form of a flood-based routing protocol: when two nodes meet, they identify the packages that the other node has and it does not have so that at the end of the process, the two nodes have the same content in the buffer. This process is repeated each time two nodes come into contact. When a node has a copy of a message, it waits to meet the destination. In this case, the resource consumption is high, but in a high mobility network, the delay of the message transmission is short. In the current network configuration, the algorithm produces poor results due to the low number of contacts between nodes. Spray and Wait is an algorithm with two phases: one for sending messages (spray) and the other waiting for the contact with the destination node (wait). This algorithm circulates in a couple of variants: a standard one and a binary one, depending on the number of spread copies of the message. It acts similar to Epidemic, with an important difference: the number of spread copies is constant. The spray phase of the standard approach consists of spraying L copies of the message by the source node itself. The spray phase of the binary approach consists of spraying half of the number of copies to a meeting node. In this case, not only the source sprays messages, but also every node that has more than one copy does the same. The nodes that have only one copy enter the waiting phase. This algorithm has the disadvantage that nodes must keep track of movements of other nodes, but the advantage is that the level of flooding is limited. PRoPHET is similar to Epidemic, too, except that it uses information from the buffer of the other node to update its predictability vector. Each node calculates the predictability of the message delivery and sends the message further only if the contact node has higher predictability than its own. The problem of this approach is the relationship between the overhead ratio and the number of nodes--as the number of nodes increases, the overhead ratio increases [16]. This protocol is known for its complexity of the forwarding strategy. Thus, it consumes a lot of resources to process and store historical values. It is feasible for networks with high computation and infrastructure capabilities. MaxProp is an algorithm based on prioritizing packet transmission and discarding. The packets in the queue are divided into two categories: those below the \"n\" hop threshold (up to that point) and those above this threshold. Newer packages that have not traveled too far are considered a priority, and the guarantee that they will reach their destination is considered to be high. In this algorithm, there is a need for high computation and infrastructure capabilities.