## 5 Issues Relating to the Fundamental Design Aspects
### UAV Flight and Trajectory  
In this section, issues pertaining to UAV flight and trajectory are discussed. To guarantee data freshness, it is very important to ensure efficient UAV trajectory optimization [2], especially for UAVs that can cover a larger area (having higher coverage radius) as they would generally require a shorter time for data collection [80]. Particularly, the packet expiration rate in such applications is connected to the flight time between the sensor nodes, and the flight order of the UAV. In this case, the UAV flight time constitutes the upper bound of the AoI for expired packets [83]. Guaranteeing data freshness in UAV-assisted IoT can be quite challenging because UAVs have to fly from one location to another while meeting the requirements of an overall network-wide objective. Applications such as environmental and health monitoring, as well as safety protection, thus require thorough trajectory planning and AoI characterization as outdated information may lead to erroneous decisions or catastrophic disasters. This makes it very important to properly design the trajectory of UAVs for time-sensitive applications [2]. Practically, traveling latency is greater than offloading latency, hence, UAVs should be made to fly close to IoT devices to achieve a higher data transmission rate. However, this implies that only a few can be served simultaneously, thus motivating the need to select hovering spots for UAVs. Similarly, in this case, the energy required for IoT devices to transmit in the uplink increases, and the same for the uploading latency. Several approaches can be used to reduce flight time while also saving energy. UAVs can stop at specific points within the network where sensor nodes can upload data before the UAV flies to another location. These locations (stopping points) provide performance gains with respect to UAV flight time reduction. Similar to this is the use of CPs, whose positions constitute the UAV's stopping or hovering points that largely determine the flight time and trajectory. Sensor nodes can transfer sensed information to another sensor node functioning as cluster heads (or CP). The information is then transmitted to the UAV (when the UAV hovers above it) based on a schedule. Using CPs has other advantages, for instance, whenever there is an overlap in the coverage area of ground nodes, the UAVs can collect data from those nodes when they fly or hover above or across the area. The rationale for using CPs is to save energy and reduce flight time. In network architectures with many CPs, optimizing the total number of CPs or reducing them is important to achieve an age-optimal UAV trajectory (see [91]). Architectures involving CPs are sometimes challenging to optimize, especially when the number of CPs could change in every round (see [84]). As mentioned earlier, using CPs can significantly help improve the age-optimal trajectory, thereby reducing flight time. Sensor nodes functioning as CPs or heads of clusters would contribute to evident performance trade-offs. In many cases, the distance between the sensor nodes and the CP is large, significantly increasing the uploading time. Sensor nodes functioning as CPs or heads of clusters would contribute to evident performance trade-offs. In many cases, the distance between the sensor nodes and the CP is large, which significantly increases the uploading time (see [84]), thus affecting the information age. Flight trajectory can be viewed as a permutation of the number of CPs to be visited and the data center. It is also possible that multiple devices can be selected in each flight turn, which necessitates proper trajectory planning [86]. Many papers have considered a clustered or CP-based architecture. For instance, a UAV takes off from the data center and flies above each CP until data gathering is over. It returns to the data center for data analysis to be carried out [84]. Whenever there is a large set of potential devices or CPs to be visited, the devices to be visited are selected first before determining the order of visits.