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Collaboration between multiple Unmanned Aerial Vehicles (UAVs) to set up a Flying Ad Hoc Network (FANET) is a growing trend since future applications claim for more autonomous and rapid deployable systems. The user experience on watching videos transmitted over FANETs should always be satisfactory even under influence of topology changes caused by the energy consumption of UAVs. In addition, the FANET must keep the UAVs cooperating as much as possible during a mission. However, one of the main challenges in FANET is how to mitigate the impact of limited energy resources of UAVs on the FANET operation in order to monitor the environment for a long period of time. In this sense, UAV replacement is required in order to avoid the premature death of nodes, network disconnections, route failures, void areas, and low-quality video transmissions. In addition, decision-making must take into account energy consumption associated with UAV movements, since they are generally quite energy-intensive. This article proposes a cooperative UAV scheme for enhancing video transmission and global energy efficiency called VOEI. The main goal of VOEI is to maintain the video with QoE support while supporting the nodes with a good connectivity quality level and flying for a long period of time. Based on an Software Defined Network (SDN) paradigm, the VOEI assumes the existence of a centrailized controller node to compute reliable and energy-efficiency routes, as well as detects the appropriate moment for UAV replacement by considering global FANET context information to provide energy-efficiency operations. Based on simulation results, we conclude that VOEI can effectively mitigate the energy challenges of FANET, since it provides energy-efficiency operations, avoiding network death, route failure, and void area, as well as network partitioning compared to state-of-the-art algorithm. In addition, VOEI delivers videos with suitable Quality of Experience (QoE) to end-users at any time, which is not achieved by the state-of-the-art algorithm.

In recent years, with the growth in the use of Unmanned Aerial Vehicles (UAVs), UAV-based systems have become popular in both military and civil applications. The lack of reliable communication infrastructure in these scenarios has motivated the use of UAVs to establish a network as flying nodes, also known as Flying Ad Hoc Networks (FANETs). However, the high mobility degree of flying and terrestrial users may be responsible for constant changes in the network topology, which makes more challenging to guarantee their communication during the operational time. In this context, this article presents a Software-defined networking (SDN) based Topology management for FANETs-called of STFANET-, which is a coordination protocol that englobes both an efficient SDN-based UAV communication and a set of topology management algorithms. The goal is to establish and maintain a FANET topology in order to provide a constant and reliable communication link among independent nodes-which are performing individual or collaborative missions-through relays units. Simulation results show the efficiency of the proposed protocol in order to provide communication in a dynamic scenario. Considering its use in a military setting, STFANET managed to achieve 25% of packet loss in transmitting data packets, 1.5ms of latency and 71% of connectivity on average. INDEX TERMS FANET, topology management, relay node placement, SDN, communication protocol.

Collaboration between multiple Unmanned Aerial Vehicles (UAVs) to establish a Flying Ad-hoc Network (FANET) is a growing trend since future applications claim for more autonomous and rapidly deployable systems. In this context, Software-Defined Networking FANET (SDN-FANET ) separates the control and data plane and provides network programmability, which considers a centralized controller to perform all FANET control functions based on global UAV context information, such as UAV positions, movement trajectories, residual energy, and others. However, control message dissemination in an SDN-FANET with low overhead and high performance is not a trivial task due to FANET particular characteristics, i.e., high mobility, failures in UAV to UAV communication, and short communication range. With this in mind, it is essential to predict UAV information for control message dissemination as well as consider hierarchical network architecture, reducing bandwidth consumption and signaling overhead. In this article, we present a Cluster-bAsed control Plane messages management in sOftware-defined flying ad-hoc NEtwork, called CAPONE. Based on UAV contextual information, the controller can predict UAV information without control message transmission. In addition, CAPONE divides the FANET into groups by computing the number of clusters using the Gap statistics method, which is input for a Fuzzy C-means method to determine the group leader and members. In this way, CAPONE reduces the bandwidth consumption and signaling overhead, while guaranteeing the control message delivering in FANET scenarios. Extensive simulations are used to show the gains of the CAPONE in terms of Packet Delivery Ratio, overhead, and energy compared to existing SDN-FANET architectures.Sensors 2020, 20, 67 2 of 18 humans' eyes in the sky, and UAVs must be flying and monitoring events in a coordinated fashion for a long period with reliability [10].In FANET scenarios, UAVs must collaborate, and their behaviors (both the data transmission and the UAV movement) must be effectively controlled to maximize the FANET benefits and application performance [11]. In this way, a decentralized approach [6] to manage FANET include more complexity to synchronize information with all network nodes, requiring more control messages to be transmitted across the FANET, and can increase total power consumption. On the other hand, a centralized UAV controlling system can make optimized decisions based on the global UAV context information [12]. A centralized controller node must deal with the mobility trajectory of UAVs to avoid UAV collisions or improve application performance. It also needs to determine data routing paths, change packet transmission parameters (data rate or transmission power) due to performance or energy reasons. Hence, FANET could be managed by a Software Defined Network (SDN) [13] composed by a group of UAVs with a central controller entity [14]. In turn, implements the concept of SDN into FANET to separate the control and data plane, and to provide network p...

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The increasing computational capacity of multiple devices, the advent of complex applications, and data generation create new challenges of scalability, ubiquity, and seamless services to meet the most diverse network demands and requirements, such as reliability, latency, battery lifetime. For this reason, the 5th Generation (5G) network comes to mitigate the most diverse challenges inherent to the current dynamic mobile networks and their increasing data rates. Unmanned Aerial Vehicles (UAVs) have also been considered as communication relays or mobile base stations to assist mobile users with limited or no available wireless infrastructure. They can provide connections for mobile users in hard-to-reach areas, replacing damaged or overloaded ground infrastructure and working as mobile clouds, providing low but increasing computational power. However, the feasibility of a Flying Edge Computing requires special attention in terms of resource allocation techniques, cooperation with existing ground units and among multiple UAVs, coordination with user mobility, computation efficiency, collision avoidance, and recharging approaches. Thus, the cooperation among UAVs and the current terrestrial Mobile Edge Computing can be relevant in some cases once the computation power of a single UAV might be insufficient. It is important to understand the feasibility of current proposals and establish new approaches that consider the usage of multiple UAVs and recharging approaches.In this paper we discuss the challenges of a 5G extended network through the help of UAVs. The proposed multi-tier architecture employs UAVs with different mobility models, providing support to ground nodes. Moreover, the support of the UAVs as edge nodes will also be evaluated.

Many of the new mobile communication devices will be things that power and monitor our homes, city infrastructure and transport. Controlling drones thousands of miles away, performing remote surgeries or being immersed in video with no latency will also be a huge game changer. Those are some of the few things that make the fifth generation (5G) a revolution expected to be a thrust to the economy. To that end, the design and density of deployment of new networks is also changing becoming more dense, what introduces new challenges into play. What else will it add to previous generations? The MOOC about Ultra-dense networks for 5G and its evolution has been prepared by the researchers of an European MSCA ITN, named TeamUp5G, and introduces the most important technologies that support 5G mobile communications, with an emphasis on increasing capacity and reducing power. The content spans from aspects of communication technologies to use cases, prototyping and the future ahead, not forgetting issues like interference management, energy efficiency or spectrum management. The aim of the MOOC is to fill the gap in graduation and post-graduation learning on content related to emerging 5G technologies and its applications, including the future 6G. The target audience involves engineers, researchers, practitioners and students. This paper describes the content and the learning outcomes of the MOOC, the main tasks and resources involved in its creation, the joint contributions from the academic and non-academic sector, and aspects like copyright compliance, quality assurance, testing and details on communication and enrollment, followed by the discussion of the lessons learned.