UC Irvine

Autonomous networks of unmanned aerial vehicles (UAVs) have many civilian and military applications. These networks experience a wide variety of network configurations and communication constraints (including node density, speed, and trajectory), resulting in a highly dynamic and unpredictable network topology. In addition, these networks support diverseand time-varying applications that can include different traffic types and priorities, data generation rates, session lengths, and reliability and latency tolerance.

In this dissertation, we develop distributed, cross-layer medium access control (MAC) and routing protocols to provide robust and reliable communication in autonomous and decentralized UAV networks, in which the network topology and traffic conditions change frequently and the future node trajectories are not known.

First, we present a mathematical framework to compute the link lifetime for a realistic node mobility model, followed by the design of a novel, distributed time division multiple access (TDMA) scheme for directional communication in multihop networks. This scheme includes a low-complexity, rank-based scheduling mechanism, which effectively adapts to the changes in the network and quality of service (QoS) demands in real-time with significantly reduced overhead and delay, and improves both channel utilization and fairness in channel access allocation.

In the subsequent chapters, we focus on routing protocols, which discover and select high-quality routes, and switch to alternate routes in response to changes in the available communication resources, observed traffic patterns, and performance demands to make the best use of the network resources.

Traditional topology-based routing schemes are slow to adapt to changes in topology and traffic, and typically select a route without considering the effect of intra-flow interference on the selected route. To address these issues, we present an adaptive, cross-layer, mobility and congestion-aware proactive routing protocol for decentralized UAV networks. Our protocol includes a novel, multi-step and multi-metric, inter- and intra-flow interference-aware route selection mechanism, which selects a stable, longer-lasting and less congested route. It uses a preemptive route switching mechanism to prevent potential packet drops due to congestion and topology changes, and a periodic queue management mechanism to prioritize transmitting packets with a lower survivability score, and discard packets that are likely to expire before reaching their destination.

Proactive routing protocols can incur large control and computational overhead, and may be vulnerable to the security threats. In contrast, reactive routing protocols incur much lower control and computation overhead, but the resulting, on-demand route discovery introduces large routing overhead and delay in settings with frequent topology changes and link breaks, such as UAV networks. We address these issues via a novel, hybrid mobility- and congestion-aware reactive routing protocol, which discovers routes on demand and preemptively switches to another high-quality route within the region around the selected route. This significantly reduces the number of route discoveries and overhead from route control and computation. Despite having limited network topology information, our proposed routing scheme providessuperior flow throughput performance.

We show via network simulation results that our proposed MAC and routing protocols significantly outperform existing schemes across a variety of different network and traffic settings.