Airborne networks (AN) consisting of low SWaP (size, weight, and power) fixed-wing unmanned aerial vehicles (UAVs) are widely used in various civilian and military applications, such as environmental sensing, disaster management, area monitoring, surveillance, search and rescue, and tracking. These networks are generally characterized by highly dynamic and unpredictable network topology due to varying node density, high speed, and dynamic trajectories. In addition, they should support diverse applications with different types of data traffic, data rates, flow priorities, reliability, and latency tolerance, in order to provide a high quality of service (QoS).
To carry out the above operations effectively, a scalable, decentralized, autonomous UAV network architecture with high network connectivity is required. In these applications, quick area coverage is necessary for promptly sensing the area, and strong node degree and base station (BS) connectivity are needed for UAV control and coordination and for transmitting sensed information to the BS in real time. However, maintaining connectivity can restrict the UAVs' ability to explore, as there is a fundamental trade-off between area coverage and connectivity.
In this dissertation, we develop distributed, connectivity-aware UAV mobility models and robust reactive routing protocols, followed by a route repair scheme to provide efficient area coverage, network connectivity, and robust data transmission in autonomous, decentralized low SWaP UAV networks.
First, we design node degree and BS connectivity-aware distributed pheromone mobility models that maintain a desired connectivity among 1-hop neighbors and to the BS while achieving fast area coverage to promote autonomous coordination of UAV movements in a decentralized UAV network and transmit sensed information to the BS over multi-hop routes. These heuristic models are followed by the design of deep Q-learning based connectivity-aware mobility models to further tune and improve the coverage and connectivity trade-off. Since it is not practical to know the complete topology of a decentralized network in real time, the proposed mobility models work online, are fully distributed, and rely only on local neighborhood information. Our simulations demonstrate that our proposed mobility models achieve efficient area coverage and desired node degree and BS connectivity, improving significantly over existing schemes.
Routing protocols help in transmitting the sensed data from UAVs monitoring the targets (called target UAVs) to the BS. However, the highly dynamic nature of an autonomous, decentralized UAV network leads to frequent route breaks or traffic disruptions. Traditional routing schemes cannot quickly adapt to dynamic UAV networks and/or incur large control overhead and delays. To establish stable, high-quality routes from target UAVs to BS, we design a hybrid reactive routing scheme called pipe routing that is mobility, congestion, and energy-aware. The pipe routing scheme discovers routes on-demand and proactively switches to alternate high-quality routes within a limited region around the active routes (called pipe) when needed, thus reducing the number of route breaks and increasing data throughput.We then design a novel topology control-based pipe routing scheme to maintain robust connectivity in the pipe region around the active routes, leading to improved stability of routes and increased throughput with minimal impact on the coverage performance of the UAV network.
Finally, we design a local route repair scheme for airborne networks consisting of nodes equipped with multibeam antennas and operating in frequency division duplex (FDD) communication mode, where multipath routes can be formed between a pair of source and destination nodes to support bidirectional traffic. Here, every forward and reverse route completely overlaps. The proposed scheme improves the network performance (in terms of data throughput, latency, and overhead) by locally repairing the routes while preserving the overlapping and link-disjoint (or node-disjoint) characteristics of these routes.
We show via network simulation results that our proposed connectivity-aware UAV mobility, routing with topology control, and local route repair schemes achieve significantly better performance compared to existing schemes.
