Dynamic Routing for Flying Ad Hoc Networks (1406.4399v3)

Abstract: This paper reports experimental results on self-organizing wireless networks carried by small flying robots. Flying ad hoc networks (FANETs) composed of small unmanned aerial vehicles (UAVs) are flexible, inexpensive and fast to deploy. This makes them a very attractive technology for many civilian and military applications. Due to the high mobility of the nodes, maintaining a communication link between the UAVs is a challenging task. The topology of these networks is more dynamic than that of typical mobile ad hoc networks (MANETs) and of typical vehicle ad hoc networks (VANETs). As a consequence, the existing routing protocols designed for MANETs partly fail in tracking network topology changes. In this work, we compare two different routing algorithms for ad hoc networks: optimized link-state routing (OLSR), and predictive-OLSR (P-OLSR). The latter is an OLSR extension that we designed for FANETs; it takes advantage of the GPS information available on board. To the best of our knowledge, P-OLSR is currently the only FANET-specific routing technique that has an available Linux implementation. We present results obtained by both Media Access Control (MAC) layer emulations and real-world experiments. In the experiments, we used a testbed composed of two autonomous fixed-wing UAVs and a node on the ground. Our experiments evaluate the link performance and the communication range, as well as the routing performance. Our emulation and experimental results show that P-OLSR significantly outperforms OLSR in routing in the presence of frequent network topology changes.

• The paper evaluates predictive-OLSR (P-OLSR) and traditional OLSR for Flying Ad Hoc Networks (FANETs), incorporating GPS-based metrics into P-OLSR to predict link quality in high-mobility scenarios.
• Experiments with UAVs and large-scale simulations demonstrated P-OLSR's superior performance over OLSR, significantly reducing datagram loss rates and outage times by up to 95% amid rapid topology changes.
• The research highlights that leveraging real-time UAV telemetry for routing is a promising method to enhance FANET robustness and opens avenues for future work on scalability and integration with predictive analytics.

Dynamic Routing for Flying Ad Hoc Networks: An Evaluation of P-OLSR

Flying Ad Hoc Networks (FANETs), consisting of small unmanned aerial vehicles (UAVs), represent a promising paradigm for swiftly deployable, cost-effective communication systems in both civilian and military domains. Given their elevated mobility compared to traditional Mobile Ad Hoc Networks (MANETs), FANETs necessitate specialized routing protocols capable of adapting to rapidly changing network topologies. The paper "Dynamic Routing for Flying Ad Hoc Networks" critically evaluates the performance of two routing protocols: the conventional Optimized Link State Routing (OLSR) and a FANET-specific extension, predictive-OLSR (P-OLSR).

The P-OLSR protocol enhances OLSR by incorporating GPS-based metrics to predict link quality variations, aiming to improve routing decisions amid frequent topology changes. This adaptation of the expected transmission count (ETX) metric considers UAV relative velocities to better anticipate route reliability. Notably, this approach addresses a significant limitation observed in MANET protocols, whereby high mobility and topology volatility lead to suboptimal performance.

Experimental Setup and Results

The paper employs both MAC layer emulation and real-world experiments to evaluate the two protocols. The field experiments utilized a testbed consisting of fixed-wing UAVs, namely eBees, and a ground node, with P-OLSR demonstrating superior adaptability to topology changes compared to traditional OLSR. The routing adjustments in P-OLSR ensured a lower datagram loss rate (DLR) and maintained seamless communication without service interruptions, which OLSR could not achieve due to its delayed response to link breakages.

Furthermore, larger network simulations involving 19 UAVs revealed that P-OLSR considerably reduced outage times compared to OLSR, with outage reductions of up to 95% in certain configurations. This finding underscores the enhanced robustness of P-OLSR in managing dynamic network conditions typical of FANET deployments.

Theoretical and Practical Implications

The integration of real-time UAV telemetry into routing protocols, exemplified by P-OLSR, is a compelling development in ad hoc network research. It offers a viable pathway to overcoming inherent mobility and connectivity challenges in FANETs. This research suggests that leveraging onboard GPS information not only enhances link quality assessments but also potentially reduces the routing overhead associated with static protocol parameters, thereby optimizing resource utilization.

Future Directions

This paper lays a foundation for further exploration of GPS-assisted routing improvements in high-mobility scenarios. Future research could focus on the scalability of P-OLSR in even larger networks with varied node speeds and flight patterns. Moreover, investigating the integration of predictive analytics with machine learning algorithms for adaptive routing could provide new dimensions of efficiency and reliability in FANET operations.

In conclusion, the research convincingly demonstrates the benefits of tailoring routing protocols to specific network dynamics in FANETs. By embracing predictive metrics derived from GPS data, P-OLSR represents a significant advancement over existing MANET solutions, setting a precedent for future innovations in UAV-based communication networks.