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.

翻译：无人机是一种嵌入式系统（ES），广泛应用于从摄影到货物运输乃至危机管理中的搜索、救援和损害评估活动等多个领域。然而，其有限的电池续航能力和高能耗是极为关键的挑战，特别是在多架无人机需与地面基站（GBS）通信的网络化系统中。本研究针对这些限制，提出了一种面向无人机集群的生物启发式基于领导者的能量管理系统。该算法受生物行为模型启发，动态选择集群中的单一无人机作为领导者，负责与GBS进行远距离通信，从而使其他无人机能够节省能量。通过改变网络规模和配置，评估了所提出的生物启发式算法的有效性。结果表明，我们的方法通过消除无谓的能耗通信，显著提高了网络效率和服务时间。