Scheduling UAVs to bridge communications in delay-tolerant networks using real-time scheduling analysis techniques

We present an approach to utilising unmanned aerial vehicles (UAVs) as communication relays, in which a dynamic positioning algorithm drives UAVs automatically to achieve the best incoming and outgoing signal strength and packet throughput among participating ground nodes. This approach can be applied to real-life scenarios with widely distributed communicating nodes, for example, disasters like earthquakes with damaged communication towers, and harvesting sensor readings from distributed sensor nodes. UAVs can establish a direct communication link between multiple nodes if they are within communication ranges to the UAVs. If this is not possible, the UAVs may be scheduled to bridge communications between the nodes with some time delay. In other words, a delay tolerant network (DTN) among participating nodes can be formed whereby the UAVs fly over the nodes to collect, buffer and deliver data. This is useful in scenarios such as harvesting data from a widely distributed sensor network (e.g., flood monitoring in jungle). We provide a scheduling analysis framework to show if a UAV can cover a given set of distributed nodes. Each sensor node may have a different priority, required frequency of visits and communication range. The framework was inspired by the response-time analysis approach for scheduling tasks in the real-time scheduling literature. In essence, we analyse the worst-case response time and schedulability for a UAV to visit and process communication requests for the lowest priority node among the participants. We also demonstrate that this approach can interact with a physics simulator that models wind speed and turbulence, and learn and optimise on possible routes and positions for UAVs.