# UAV Support for Mission Critical Services
## 3 UAV Characteristics, Classifications and Commercial Deployments Status
### UAVs as a Part of the Communication Infrastructure  
The UAVs are already in use in handling disasters. Their primary role is inspection, surveillance or transporting relatively small parcels. It is expected that their role will grow. In this section, we focus on the support of MCS by UAVs, i.e., using UAVs to provide on-demand communications in specific areas to replace the malfunctioning communication infrastructure (due to disaster or power grid failure). The use of UAVs as a part of communication and computing infrastructure is not new. In the literature, many approaches can be found in which UAVs are used to extend the mobile network coverage or to be used as mobile MEC hosts. The idea of incorporating UAVs into mobile network architecture is pretty popular; for example, UAVs as relays of 4G or 5G networks are described in [36]. In [15] a disaster resilient architecture that consists of an SDN that provides centralized traffic redirection and resource management, a UAV-based cloudlet (small data centre) to facilitate edge computing for LTE access networks is presented. In [37], an evaluation study related to UAV-assisted network, RAN and cloud service enhancements are presented. In the concept, the UAVs may play the role of flying 5G nodes. The authors assumed that UAV can act as gNB (Remote Radio Head (RRH), Centralised Unit (CU), Distributed Unit (DU)) or Network Function (NF) of 5 GC. The UAV can also provide heterogeneous access to the WiFi (WiFi) access and Disruption Tolerant Networking (DTN) functionalities. In many described cases, the UAVs are incorporated into the MEC platform, reducing the overall delay and amount of data to be transmitted to a central cloud. This particularly concerns IoT time-critical solutions. In [38], the role of UAV computing as an intelligent edge cloud combined with AI for handling search and rescue actions was emphasized. In the AGMEN concept [39] the UAVs assist the communication, caching and computing at the edge of the network. Many approaches to UAV-based computing are presented in [40; 41]. The UAVs may form an ecosystem with other NTN solutions. A review of using NTN, including HAPS, LEO and MEO satellites and UAVs as cooperating components of 6G networks is described in [42]. In some concepts, UAVs are part of network slices. In [43], a 5G network slice for video monitoring with a Flying Ad-hoc NETwork (FANET) constituted by UAVs and Multi-access Edge Computing (MEC) was described (see Figure 3). The proposed approach aims to improve reliability and decrease the latency between sources and actuators. To optimize the behaviour of such a solution, AI-based algorithms are proposed. A comprehensive review of the routing protocols and mobility models for Flying Ad hoc Networks (FANETs) is presented in [44]. This concept applies to a group of UAVsand includes many protocols developed for Mobile Ad hoc Network (MANET). FANET allows forming a mesh topology between UAVs and finding a path between two arbitrary UAVs. Using Q-learning, the problem of optimized placement of UAVs used as Aerial Base Stations (ABSs) was addressed in [45]. ABS can be static or mobile, and they can adjust their position according to the users' actual location. Please note that the papers on computing-enabled UAVs describe such systems' functional capabilities but completely ignore the orchestration process. The orchestration in such an environment due to wireless, relatively low-bitrate and unreliable links requires a particular approach. The UAV computing resources are constrained, which makes the classical Management and Orchestration (MANO) orchestration not applicable in such a case. The orchestration operations (transfer of containers, virtual machines or MEC Apps) consume the radio link bandwidth, disturbing that way the implemented services. This is the issue that has been neglected in the above-mentioned UAV-related papers, and this is partly addressed in [46]. Using UAVs as mobile nodes is simple, according to the UAV characteristic provided in the chapter in a baseline solution.