# Cooperative UAV Scheme for Enhancing Video Transmission and Global Network Energy Efficiency
## 2 Related Work  
Surveillance and monitoring is a kind of service where camera-equipped UAVs are increasingly present. In the related environment, the high QoE of video transmitted is crucial to take a correct and precise decision, mainly in an emergency situation. The work presented by [PERSON] et al. [14] shows a mechanism called of mobiFANET, which assists relay node replacement in order to guarantee a reasonable video distribution that consequently increases the QoE. MobiFANET takes into account the UAV location and mobility trajectory to establish the ideal relay node location, keeping the connectivity between neighbor UAVs of a given path, mitigating the effects of UAV mobility, avoiding communication flaws, delays, and void area. MobiFANET also mitigates the effects of UAV mobility, avoiding communication failures, delays, and empty areas. However, the limited view of the UAVs resources does not allow rearrange the FANET to provide further UAVs energy replenishment regarding maintaining QoE. [PERSON] et al. [15] highlighted the main research topics about exiting UAV and aquatic vehicles. Regarding communication technology, the main advantage of IEEE 802.15.4 is energy saving compared to IEEE 802.11. The first technology takes the advantage from the lower transmission rate to avoid extra energy loss in communication. However, the adoption of IEEE 802.11 is more feasible for video transmission despite the energy consumption. Another advantage is the longer distance that can be reached in a environment that the nodes can be placed far from each other. Moreover, it also demands fewer requirements when compared to satellite communications. In addition, [PERSON] [16] proposed a Wireless Mesh Networks design composed by UAVs, assuming batteries and Access Points are replaceable and separable from UAVs and both are transported and placed in appropriate positions by the mechanical automation of UAVs. The UAV nodes are equipped with IEEE 802.11g due to its simplicity to determine the channel model and transmission rate. In addition, each node works as AP and is positioned in order to enhance the network throughput. [PERSON] et al. [17] presented an overview of the main characteristics of FANET. The work presents the state-of-the-art about mobility, positioning and propagation models adopted. However, the focus is on the limitations of the propagation model, which has a great impact on the communication among UAVs and consequently on network lifetime. A case study is also presented and showed the impact of radio propagation on UAV to UAV, and on UAV to Ground communication, showing that the chassis decreases 10 dB the power of radio in UAV to Ground links. [PERSON] et al. [11] introduced the Software-Defined UAVNet architecture (SD-UAVNet), which implements the concept of SDN into UAVNets to separate the control and data plane, as well as to provide network programmability by controlling UAVs operation parameters. The SD-UAVNet controller considers the global UAV context information to prevent UAV collisions, optimize the UAVs' movements, and establish a routing path, which determines the relay node deployment to provide video transmission with QoE support. However, SD-UAVNet does not consider any mechanism to provide energy-efficiency operations, such as UAV replacement. [PERSON] et al. [18] proposed a UAV deployment scheme based on evolutionary algorithms. The idea is to provide Internet connectivity to users in a rural disaster scenario. The approach is divided into two phases, namely initial and adaptation phases. In the initial phase, the UAV network is deployedby taking into account only partial information. On the other hand, in the adaptation phase, the UAVs move according to a searching algorithm in order to stay in a better coverage area to attend the users. The decision-making in the initial phase runs in a centralized fashion, once it requires a high computational power to run a Genetic Algorithm. It aims to find a suitable position for the UAVs with limited information.