WiSwarm: Age-of-Information-based Wireless Networking for Collaborative Teams of UAVs

TL;DR

This paper introduces an AoI-based middleware for WiFi networks that enhances information freshness and tracking accuracy in UAV swarms, demonstrating significant improvements over traditional protocols, especially under high load and larger scale.

Contribution

The work develops and experimentally evaluates a novel AoI-based middleware for WiFi that improves data freshness and UAV tracking accuracy in real-world scenarios.

Findings

Improves information freshness by up to 109x compared to WiFi-UDP.

Enhances tracking accuracy by up to 6x over WiFi-TCP.

Performance gains increase with system scale and traffic load.

Abstract

The Age-of-Information (AoI) metric has been widely studied in the theoretical communication networks and queuing systems literature. However, experimental evaluation of its applicability to complex real-world time-sensitive systems is largely lacking. In this work, we develop, implement, and evaluate an AoI-based application layer middleware that enables the customization of WiFi networks to the needs of time-sensitive applications. By controlling the storage and flow of information in the underlying WiFi network, our middleware can: (i) prevent packet collisions; (ii) discard stale packets that are no longer useful; and (iii) dynamically prioritize the transmission of the most relevant information. To demonstrate the benefits of our middleware, we implement a mobility tracking application using a swarm of UAVs communicating with a central controller via WiFi. Our experimental results show that, when compared to WiFi-UDP/WiFi-TCP, the middleware can improve information freshness by a factor of 109x/48x and tracking accuracy by a factor of 4x/6x, respectively. Most importantly, our results also show that the performance gains of our approach increase as the system scales and/or the traffic load increases.