# Cooperative UAV Scheme for Enhancing Video Transmission and Global Network Energy Efficiency
## 2 Related Work
### Network and System Model  
FANETs will be an important resource in smart cities to monitor events by transmitting video flow from the UAVs to the ground team or service, for instance, monitoring an earthquake or hurricane, as depicted in Figure 1. In this way, video captured from the event area enable humans (or even a service) in the control center to take appropriate action based on rich visual information in order to explore a hazardous area, where rescuers are unable to reach easily and quickly. We consider the concept of SDN applied into FANET, such as introduced by [PERSON] et al. [11]. In this sense, the SDN paradigm provides flexibility to network management by separating the network infrastructure into distinct planes, where each plane can be programmed to meet particular application requirements [21]. Following the SDN paradigm, we consider four planes (application, control, forwarding, and management planes), and a centralized controller node as shown in Figure 2.  
The application plane is on the top of the proposed architecture to support multimedia applications in FANET scenario. On the other hand, the forwarding plane is located at the bottom of the SDN architecture and it is composed of (re)configurable nodes connected to a centralized controller. The control plane is located at the middle of the network architecture, which provides functions that determine the behavior and performance of the network. The Controller Node \((CN)\subset V\) is responsible for all control functions for managing the mission-specific decisions, such as UAVs replacement, routing, and others. The controller \(CN\) could be a ground station or a regular UAV node. For instance, a fixed-wing UAV has more energy and larger radio range, which can periodically collect UAV information and send configuration commands. In addition, for large-scale environments, it might be necessary to deploy multiple local Controller nodes that are responsible only to forward the control message to/from the main \(CN\). This enables the proposed scheme, to transmit control messages  
Figure 1: Video dissemination over FANET for disaster recovery scenario. with lower transmission power, which leads to reduced interference and energy consumption, as well as better control message reliability. In this multimedia FANET scenario, we consider \(n\) UAVs (nodes) deployed in the monitored area, and each UAV has an individual identity (\(i\in[1,n]\)). Those UAVs are represented in a dynamic graph \(G(V,E)\), where the vertices \(V=\{v_{1},\cdots,v_{n}\}\) mean a finite set of UAVs, and edges \(E=\{e_{1},\cdots,e_{n}\}\) build a finite set of asymmetric wireless links between 1-hop UAV \((v_{i})\) neighbors. We denote \(N(v_{i})\subset V\) as a subset of all 1-hop neighbors within the radio range \((R_{max})\) of a given UAV \(v_{i}\). Each UAV \(v_{i}\) has a queue (\(Q\)) with a maximum queue capacity (\(Q_{max}\)). The queue policy schedules the packet transmission by using the First In First Out (FIFO) algorithm and drops packets using the Drop Tail algorithm. Each UAV \(v_{i}\) is equipped with a camera, an image encoder, a radio transceiver, and limited energy supply. For convenience of notation, we denote \(SN\subset V\) (Source Node) as the UAV \(v_{i}\) responsible for capturing video flows and transmitting them to the Destination Node \((DN)\subset V\), i.e., ground station, in a multi-hop fashion via multiple relay nodes (\(RN_{i}\subset V\)). We assume a FANET scenario composed of one static \(DN\) equipped with a radio transceiver, an image decoder, and unlimited energy, which is responsible for receiving the video for further processing and dissemination. Each UAV \(v_{i}\) is aware of its own location \(L(X_{i},Y_{i})\) by means of a positioning system, e.g., GPS or Galileo. On the other hand, the location of the \(DN\) is assumed to be known a priori by each node \(v_{i}\), since it is a static node.