Simulating Situational Overview in Large-Scale UAS Networks Using Demand Driven Mobility

Recently, Rate Decay Flooding (RDF) has been proposed as a special-purpose protocol to facilitate network-wide information exchange in large-scale urban Unmanned Aircraft System (UAS) networks. Nevertheless, mobility is a crucial aspect determining the performance of these protocols. In this work, we use randomly generated city geometries and flight demands to simulate Demand Driven Mobility (DDM) that represents plausible trajectories for a package delivery scenario in urban areas. These trajectories are then fed into a network simulator to obtain realistic performance measurements of the proposed protocols. Furthermore, we compare the results to Random Direction Mobility (RDM) widely used in UAS communication research. We quantify the performance with the dissemination rate, which is a measure of how effectively information is distributed within the network. Our results show, that even if matched for area and number of UAS, the choice of mobility has a strong influence on the performance. For low density, DDM causes temporary UAS clusters to form around drone ports that are not connected to UAS on delivery flights to the outskirts of the city, which results in a more poorly connected network compared to RDM. In high-density scenarios, where traffic is highly concentrated around drone ports, UAS located between the drone ports have to carry high amounts of data between them.