# Flying Real-Time Network to Coordinate Disaster Relief Activities in Urban Areas +
## 1 Introduction
Therefore, there is no way to ensure that two teams that require information exchange would be able to do so when required, either through a direct interaction between them or by using a WU as intermediary. Therefore, the authors also introduced the concept of _mules_[1; 12], as mobile WUs that provide real-time guarantees of message delivery between the SAR teams and the IC. These rules can be implemented by attaching computing devices to vehicles (e.g., cars, motorcycles, bicycles), and they complement the service provided by regular WUs. For instance, the route of the mules can be designed to allow information exchange not only among teams, but also among WUs. Although the use of land mules seems to solve the problem when the deadlines for the message delivery are not short, the orography of the terrain and the layout of the area usually reduce the chances to accomplish with short deadlines when required (e.g., when evacuation alarms are delivered). In this paper, we address this challenge by introducing the idea of deploying a network of flying witness units (FWUs) implemented using unmanned aerial vehicles (UAVs, also called drones). These autonomous vehicles are usually designed to primarily collect data to meet a multitude of different tasks and applications. The lack of an onboard pilot allows them to exist in a variety of sizes and forms, which offers a dizzying array of options for organizations involved with disaster relief and mitigation. These flying units can be specialized to play both of the previously discussed roles, acting as regular witness units that provide a communication link among members of a SAR team, and also as flying rules that follow a path to provide communication among disconnected teams. Moreover, the use of these units allows the communication and mobility constraints imposed by the orography of the terrain and the street layout to be reduced, and the whole network can be seen as a FANET (Flying Ad-Hoc Network) [13]. While there have been several recent research efforts on FANETs, the design and efficient deployment of these networks still represents a great challenge. In disaster scenarios, the deployment of the FANETs needs to address the real-time behavior and also show the feasibility of timely message delivery. In this sense, the proposal reported in this article also makes a contribution to this study area. This paper presents three main contributions. The first is the extension of the concept of witness units from stationary devices and land rules to flying witness units that have capacity to store-and-forward digital information between stationary and mobile teams (e.g., between SAR teams and the IC). The second contribution is the general structure proposed to implement a Flying Real-Time Network (FRTN) and the indications for its deployment in order to have a predictable behavior in message transmissions. The third contribution is the computation of real-time feasibility conditions for this kind of network, where there is no continuously available end-to-end path. This last contribution allows reducing the effort of prototyping these networks and evaluating their performance, since an analytical approach can be used instead of the typical network simulations. This article is an extended version of the proposal presented in [12]. The next section presents and discusses the related work. Section 3 introduces the system proposal, its structure, and the message transmission model. Section 4 proposes two meta-heuristics to minimize the deployment of nodes in a FRTN, while keeping the required connectivity. Section 5 presents the real-time analysis of the network model, showing that the FRTNs are able to provide stable and real-time digital communication in disaster relief scenarios. The analytic results are then compared to those obtained from simulations, thus corroborating the communication capabilities of these networks. Section 6 discusses the proposal considering real constraints, and finally Section 7 presents the conclusions and future work.