Control plane scheme for energy efficient video dissemination in Software Defined Unmanned Aircraft Networks
SDN, UAV, and QoE
In the context of Smart Cities, there is a growing claim for a more autonomous and rapidly deployable systems. Collaboration among multiple Unmanned Aerial Vehicles (UAVs) to set up a Flying Ad-Hoc Network (FANET) is a growing trend due to its capacity to support a wide range of application. Applications that work with video transmission in FANETs should always deliver a satisfactory video quality to the users even under influence of network 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 the impact of limited energy resources of UAVs can be mitigated on the FANET operation in order to monitor the environment for a long period of time. In this sense, it is required UAV replacement in order to avoid the premature death of nodes, network disconnections, route failures, void areas, and low-quality video transmissions. Moreover, decision-making must take into account energy consumption associated with UAV movements, since they are generally quite energy-intensive. This work 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 a Software Defined Network (SDN) paradigm, the VOEI assumes the existence of a centralized 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.