@inproceedings{9c9d91a62ab4401da571ca8cb3245416,
title = "Network-Aware Genetic Algorithms for the Coordination of MALE UAV Networks",
abstract = "Maintaining an ad hoc network infrastructure to cover multiple ground-based users can be achieved by autonomous groups of hydrocarbon powered medium-altitude, long-endurance (MALE) unmanned aerial vehicles (UAVs). This can be seen as an optimisation problem to maximise the number of users supported by a quality network while making efficient use of the available power. We present an architecture that combines genetic algorithms with a network simulator to evolve flying solutions for groups of UAVs. Results indicate that our system generates physical network topologies that are usable and offer consistent network quality. It offers a higher goodput than the non-network-aware equivalent when covering the communication demands of multiple ground-based users. Most importantly, the proposed architecture flies the UAVs at lower altitudes making sure that downstream links remain active throughout the duration of the mission.",
keywords = "Genetic algorithms, Networks, Unmanned aerial vehicles, Wireless communication",
author = "Alexandros Giagkos and Wilson, {Myra S.} and Ben Bancroft",
note = "Publisher Copyright: {\textcopyright} 2021, Springer Nature Switzerland AG.; 22th Annual Conference Towards Autonomous Robotic Systems, TAROS 2021 ; Conference date: 08-09-2021 Through 10-09-2021",
year = "2021",
month = oct,
day = "31",
doi = "10.1007/978-3-030-89177-0_12",
language = "English",
isbn = "9783030891763",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Nature",
pages = "116--125",
editor = "Charles Fox and Junfeng Gao and {Ghalamzan Esfahani}, Amir and Mini Saaj and Marc Hanheide and Simon Parsons",
booktitle = "Towards Autonomous Robotic Systems - 22nd Annual Conference, TAROS 2021, Proceedings",
address = "Switzerland",
}