TY - GEN
T1 - SwarmControl
T2 - 38th IEEE Conference on Computer Communications, INFOCOM 2020
AU - Bertizzolo, Lorenzo
AU - D'Oro, Salvatore
AU - Ferranti, Ludovico
AU - Bonati, Leonardo
AU - Demirors, Emrecan
AU - Guan, Zhangyu
AU - Melodia, Tommaso
AU - Pudlewski, Scott
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/7
Y1 - 2020/7
N2 - 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.
AB - 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.
KW - Distributed Network Control
KW - Drone Networks
KW - Software-Defined Networking
UR - https://www.scopus.com/pages/publications/85087427366
U2 - 10.1109/INFOCOM41043.2020.9155231
DO - 10.1109/INFOCOM41043.2020.9155231
M3 - Conference contribution
AN - SCOPUS:85087427366
T3 - Proceedings - IEEE INFOCOM
SP - 1768
EP - 1777
BT - INFOCOM 2020 - IEEE Conference on Computer Communications
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 6 July 2020 through 9 July 2020
ER -