# SwarmControl: An Automated Distributed Control Framework for Self-Optimizing Drone Networks

arXiv: https://arxiv.org/abs/2005.09781 · HTML: https://mlsanity.com/paper/2005.09781/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 19 May 2020.

## Built on by (most cited first, 4 of 4)

- [Colosseum: Large-Scale Wireless Experimentation Through Hardware-in-the-Loop Network Emulation](https://mlsanity.com/paper/2110.10617/) (2021)
- [BatMobility: Towards Flying Without Seeing for Autonomous Drones](https://mlsanity.com/paper/2307.11518/) (2023)
- [A2-UAV: Application-Aware Content and Network Optimization of Edge-Assisted UAV Systems](https://mlsanity.com/paper/2301.06363/) (2023)
- [Quantum Machine Learning for UAV Swarm Intrusion Detection](https://mlsanity.com/paper/2509.01812/) (2025)

## Abstract (arXiv)

Networks of Unmanned Aerial Vehicles (UAVs), composed of hundreds, possibly thousands of highly mobile and wirelessly connected flying drones will play a vital role in future Internet of Things (IoT) and 5G networks. However, how to control UAV networks in an automated and scalable fashion in distributed, interference-prone, and potentially adversarial environments is still an open research problem. This article introduces SwarmControl, a new software-defined control framework for UAV wireless networks based on distributed optimization principles. In essence, SwarmControl provides the Network Operator (NO) with a unified centralized abstraction of the networking and flight control functionalities. High-level control directives are then automatically decomposed and converted into distributed network control actions that are executed through programmable software-radio protocol stacks. SwarmControl (i) constructs a network control problem representation of the directives of the NO; (ii) decomposes it into a set of distributed sub-problems; and (iii) automatically generates numerical solution algorithms to be executed at individual UAVs. We present a prototype of an SDR-based, fully reconfigurable UAV network platform that implements the proposed control framework, based on which we assess the effectiveness and flexibility of SwarmControl with extensive flight experiments. Results indicate that the SwarmControl framework enables swift reconfiguration of the network control functionalities, and it can achieve an average throughput gain of 159% compared to the state-of-the-art solutions.