A Bio-Inspired Leader-based Energy Management System for Drone Fleets
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arXiv
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| Main Authors: | , , , |
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| Format: | Preprint |
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2025
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| _version_ | 1866914159806906368 |
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| author | Napoli, Rosario Celesti, Antonio Villari, Massimo Fazio, Maria |
| author_facet | Napoli, Rosario Celesti, Antonio Villari, Massimo Fazio, Maria |
| contents | Drones are embedded systems (ES) used across a wide range of fields, from photography to shipments and even during crisis management for searching, rescuing and damage assessment activities. However, their limited battery life and high energy consumption are very important challenges, especially in networked systems where multiple drones must communicate with a Ground Base Station (GBS). This study addresses these limitations by proposing the implementation of a bio-inspired leader-based energy management system for drone fleets. Inspired by bio-behavioral models, the algorithm dynamically chooses a single drone as a Leader in a cluster to handle long-range communication with the GBS, allowing other drones to preserve their energy. The effectiveness of the proposed bio-inspired algorithm is evaluated by varying network sizes and configurations. The results demonstrate that our approach significantly increases network efficiency and service time by removing useless energy consumption communications. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2511_12070 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | A Bio-Inspired Leader-based Energy Management System for Drone Fleets Napoli, Rosario Celesti, Antonio Villari, Massimo Fazio, Maria Networking and Internet Architecture 68T42 (Agent technology and artificial intelligence), 68M14 (Distributed systems) I.2.11; C.2.4 Drones are embedded systems (ES) used across a wide range of fields, from photography to shipments and even during crisis management for searching, rescuing and damage assessment activities. However, their limited battery life and high energy consumption are very important challenges, especially in networked systems where multiple drones must communicate with a Ground Base Station (GBS). This study addresses these limitations by proposing the implementation of a bio-inspired leader-based energy management system for drone fleets. Inspired by bio-behavioral models, the algorithm dynamically chooses a single drone as a Leader in a cluster to handle long-range communication with the GBS, allowing other drones to preserve their energy. The effectiveness of the proposed bio-inspired algorithm is evaluated by varying network sizes and configurations. The results demonstrate that our approach significantly increases network efficiency and service time by removing useless energy consumption communications. |
| title | A Bio-Inspired Leader-based Energy Management System for Drone Fleets |
| topic | Networking and Internet Architecture 68T42 (Agent technology and artificial intelligence), 68M14 (Distributed systems) I.2.11; C.2.4 |
| url | https://arxiv.org/abs/2511.12070 |