## 3 UAV Computing
The duration of the flight is affected by the UAV's energy consumption, which in turn affects the UAV-enabled MEC system performance. As a result, energy-efficient UAV-enabled MEC systems must be designed considering both the UAV's and mobile devices' energy usage. UAVs have the features of high mobility and ease of deployment, allowing for the provision of on-demand communication services [76]. UAVs have recently gained interest in various applications, including delivery, agricultural, emergency response, and communication services [77]. A UAV computing with on-demand mobility may deliver computing services for mobile users better in some situations than fixed communication infrastructures. The advantages of a UAV computing are underlined in situations where fixed communication infrastructures cannot meet the computing requirements of ground users, such as sites far from communication facilities and places where natural catastrophes have damaged communication infrastructure. A UAV may fly to specific locations on demand to assist users with computational needs, such as monitoring equipment, to complete tasks. UAV computing can reduce the strain of computing in specific locations due to its on-demand mobility. UAVs can be equipped with lightweight CPUs to provide computing services. As a result, UAVs fly MEC servers in the sky, supplementing existing MEC servers on the ground with controlled mobility and high-quality communication connectivity. UAVs can play various roles in offering edge computing services due to their mobility and ease of deployment. MEC designs with UAV capabilities can be categorized and assigned to a specific application situation. A UAV can function as an Edge Computing (EC) server, an IoT node, or a relay. Firstly, when UAVs transfer their computation to an MEC server, such as in [78; 79], they may participate in the system as mobile devices. Secondly, the UAV can serve as the MEC for collecting task data of mobile end nodes to perform task computation. Thirdly, the UAV can be a relay or gateway between mobile end nodes and an MEC server, relaying task data of mobile nodes to the MEC server. A UAV-enabled MEC has been proposed in response to the disadvantages of terrestrial MEC networks [80; 81], in which the edge server is installed on a UAV to allow computing offloading for users. Compared with standard terrestrial MEC networks, the UAV-enabled MEC network provided dependable LoS to users and was installed with variable mobility [82]. Furthermore, the terrestrial networks are damaged and destroyed during the disaster. Therefore, the terrestrial MEC network might be turned off (e.g., in [83]), and the UAV MEC will provide computing services to the users. Figure 2 demonstrates UAVs' deployment to support terrestrial computing and enable UAV computing for everything in the disaster area. The collaboration of multi-UAV and Search and Rescue (SAR) teams in B5G plays a vital role in improving safety and reducing the economic impacts of disaster [84; 85]. Interestingly, the authors in [86] studied a combination of roles of a single UAV in terms of edge computing functions and focused on reducing the computational complexity of a UAV-aided MEC system. In this work, the mobile users/devices have the option to compute their own tasks, offload some task bits to the UAV for computing, or the UAV can offload tasks on the devices' behalf as a relay to the terrestrial AP for computing. However, there are still some serious challenges with UAV computing. Firstly, placing the edge computing on a UAV increases the strain on the UAV and the amount of energy consumed by the propulsion system. Secondly, a UAV's battery capacity is restricted, and a UAV's service time is reduced. This is intensified by the transferring of users' computing work to the UAV, which intensifies the UAV's computation-related energy consumption. Figure 2: UAV in MEC network for disaster area.