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Metaheuristic Algorithms for UAV Trajectory Optimization in Mobile Networks

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Metaheuristics (MIC 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13838))

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Abstract

We consider a mobile network in which traditional static terrestrial base stations are not capable of completely serving the existing user demand, due to the huge number of connected devices. In this setting, an equipped Unmanned Aerial Vehicle (UAV) can be employed to provide network connection where needed in a flexible way, thereby acting as an unmanned aerial base station. The goal is to determine the best UAV trajectory in order to serve as many users as possible. The UAV can move at different speeds and can serve users within its communication range, although the data rate depends on the positions of UAV and users. In addition, each user has a demand (e.g., the number of bits the user wants to download/upload from/to the network) and a time window during which requires the service. We propose a Biased Random-Key Genetic Algorithm (BRKGA) and a Simulated Annealing Algorithm (SAA), and compare them on realistic instances with more than 500 users in different settings.

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Acknowledgements

Valentina Cacchiani acknowledges the support by the Air Force Office of Scientific Research under award number FA8655-20-1-7019.

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Authors and Affiliations

  1. DEI, University of Bologna, Viale del Risorgimento 2, 40136, Bologna, Italy

    Valentina Cacchiani, Silvia Mignardi & Chiara Buratti

  2. DPIA, University of Udine, via delle Scienze 206, 33100, Udine, Italy

    Sara Ceschia

Authors
  1. Valentina Cacchiani
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  2. Sara Ceschia
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  3. Silvia Mignardi
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  4. Chiara Buratti
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Corresponding author

Correspondence to Sara Ceschia .

Editor information

Editors and Affiliations

  1. University of Udine, Udine, Italy

    Luca Di Gaspero

  2. University of Napoli - Federico II, Napoli, Italy

    Paola Festa

  3. University of Paris Est, Paris, France

    Amir Nakib

  4. University of Catania, Catania, Italy

    Mario Pavone

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Cacchiani, V., Ceschia, S., Mignardi, S., Buratti, C. (2023). Metaheuristic Algorithms for UAV Trajectory Optimization in Mobile Networks. In: Di Gaspero, L., Festa, P., Nakib, A., Pavone, M. (eds) Metaheuristics. MIC 2022. Lecture Notes in Computer Science, vol 13838. Springer, Cham. https://doi.org/10.1007/978-3-031-26504-4_3

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  • DOI: https://doi.org/10.1007/978-3-031-26504-4_3

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-26503-7

  • Online ISBN: 978-3-031-26504-4

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