Abstract
Network slicing emerged in 5G networks as a key component to enable the use of multiple services with different performance requirements on top of a shared physical network infrastructure. A major challenge lies on ensuring wireless coverage and enough communications resources to meet the target Quality of Service (QoS) levels demanded by these services, including throughput and delay guarantees. The challenge is exacerbated in temporary events, such as disaster management scenarios and outdoor festivities, where the existing wireless infrastructures may collapse, fail to provide sufficient wireless coverage, or lack the required communications resources. Flying networks, composed of Unmanned Aerial Vehicles (UAVs), emerged as a solution to provide on-demand wireless coverage and communications resources anywhere, anytime. However, existing solutions mostly rely on best-effort networks. The main contribution of this paper is SLICER, an algorithm enabling the placement and allocation of communications resources in slicing-aware flying networks. The evaluation carried out by means of ns-3 simulations shows SLICER can meet the targeted QoS levels, while using the minimum amount of communications resources.

Abstract
The fifth generation of mobile communications networks (5G) emerges with the potential to customize the technical parameters of the same physical infrastructure for each application, service, or user, which can compromise the fundamentals that made the Internet the leading platform for dissemi-nating information and a transnational instrument of collaboration of indi-viduals and institutions. In this scenario, the present study intends to ana-lyze this new technological standard, its influence on the informational flow of the Internet, and evaluate the role of information policy for the gover-nance of the multiple interests that permeate the digital ecosystem.

Abstract
Unmanned Aerial Vehicles (UAVs) acting as Flying Access Points (FAPs) are being used to provide on-demand wireless connectivity in extreme scenarios. Despite ongoing research, the optimization of UAVs' positions according to dynamic users' traffic demands remains challenging. We propose the Traffic-aware UAV Placement Algorithm (TUPA), which positions a UAV acting as FAP according to the users' traffic demands, in order to maximize the network utility. Using a DRL approach enables the FAP to autonomously learn and adapt to dynamic conditions and requirements of networking scenarios. Moreover, the proposed DRL methodology allows TUPA to generalize knowledge acquired during training to unknown combinations of users' positions and traffic demands, with no additional training. TUPA is trained and evaluated using network simulator ns-3 and ns3-gym framework. The results demonstrate that TUPA increases the network utility, compared to baseline solutions, increasing the average network utility up to 4x in scenarios with heterogeneous traffic demands.

Abstract
5G has become increasingly popular nowadays, mainly due to its characteristics which enable high data rates and low latency. At the same time, mobile robotic platforms, such as drones and robots, appeared as suitable platforms to carry radio stations, enabling the on-demand placement of 5G communications cells. The main contribution of this paper is an obstacle-aware on-demand 5G network. The proposed solution consists of a 5G radio station (gNB) carried by a mobile robotic platform capable of providing obstacle-aware wireless connectivity to 5G User Equipments (UEs), leveraged by a novel virtual network function - On-Demand Mobility Management Function (ODMMF). ODMMF is designed to integrate the 5G Core network and it allows to monitor the radio conditions provided to the served UEs, while enabling the positioning of the mobile robotic platform remotely by taking advantage of the visual information provided by on-board video cameras. The proposed solution was validated using an experimental prototype, under a representative networking scenario.

Abstract
The ability to move and hover has made rotary-wing unmanned aerial vehicles (UAVs) suitable platforms to act as flying communications relays (FCRs), aiming at providing on-demand, temporary wireless connectivity when there is no network infrastructure available or a need to reinforce the capacity of existing networks. However, since UAVs rely on their on-board batteries, which can be drained quickly, they typically need to land frequently for recharging or replacing them, limiting their endurance and the flying network availability. The problem is exacerbated when a single FCR UAV is used. The FCR UAV energy is used for two main tasks: Communications and propulsion. The literature has been focused on optimizing both the flying network performance and energy efficiency from the communications point of view, overlooking the energy spent for the UAV propulsion. Yet, the energy spent for communications is typically negligible when compared with the energy spent for the UAV propulsion. In this article, we propose energy-aware relay positioning (EREP), an algorithm for positioning the FCR taking into account the energy spent for the UAV propulsion. Building upon the conclusion that hovering is not the most energy-efficient state, EREP defines the trajectory and speed that minimize the energy spent by the FCR UAV on propulsion, without compromising in practice the quality of service offered by the flying network. The EREP algorithm is evaluated using simulations. The obtained results show gains up to 26% in the FCR UAV endurance for negligible throughput and delay degradation.

Abstract
Unmanned Aerial Vehicles (UAVs) have emerged as adequate platforms to carry communications nodes, including Wi-Fi Access Points and cellular Base Stations. This has led to the concept of flying networks composed of UAVs as a flexible and agile solution to provide on-demand wireless connectivity anytime, anywhere. However, state of the art works have been focused on optimizing the placement of the access network providing connectivity to ground users, overlooking the backhaul network design. In order to improve the overall Quality of Service (QoS) offered to ground users, the placement of Flying Gateways (FGWs) and the size of the queues configured in the UAVs need to be carefully defined to meet strict performance requirements. The main contribution of this article is a traffic-aware gateway placement and queue management (GPQM) algorithm for flying networks. GPQM takes advantage of knowing in advance the positions of the UAVs and their traffic demand to determine the FGW position and the queue size of the UAVs, in order to maximize the aggregate throughput and provide stochastic delay guarantees. GPQM is evaluated by means of ns-3 simulations, considering a realistic wireless channel model. The results demonstrate significant gains in the QoS offered when GPQM is used.