The use of drone networks in telecommunication especially in emergency situations has been increasing during the last years. The deployment of drones in the absence of network infrastructure or in cooperation with critical ones represents an important aid to guarantee the continuity of the services toward the clients. This paper introduces a modified Link-State routing method capable of regularly updating the link status of drones and dynamically reconfiguring the network topology, as well as re-routing current and incoming calls through paths with greater available bandwidth. To determine the optimal path for transmitting traffic between source and destination drones, we propose a modified version of the Ford-Fulkerson algorithm, considering the path with the highest remaining capacity. Additionally, we integrated a simple mobility prediction mechanism into the drone’s capabilities to accelerate route pre-computation during user movement, thereby preventing and minimizing packet loss.
In recent years, there has been significant interest from the scientific community in the fields of precision agriculture assisted through the use of Unmanned Aerial Vehicles (UAVs). This paper introduces a novel system that addresses the challenge of charging station issues in a UAV network. It proposes a system based on a master/slave model where there is a master station connected to different slave stations that use a lightweight application protocol, such as MQTT, for communicating with each other. Specifically, the paper proposes a smart station design aimed at effectively managing UAV fleets by task allocation and activity scheduling. In this way, the fleet of UAVs can recharge the batteries during the mission guaranteeing the completition of the performed task and facilitating an on-demand energy supply to the UAVs that need recharging during the mission.
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