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Joint Mission Assignment and Topology Management in the Mission-Critical FANET
40
Citations
39
References
2020
Year
Joint Mission AssignmentEngineeringUav RolesUnmanned VehicleUnmanned SystemSystems EngineeringCombinatorial OptimizationNetwork OptimizationUnmanned Aerial VehiclesDesignSpace-air-ground Integrated NetworkConfiguration ManagementComputer ScienceAerial RoboticsAerospace EngineeringSpace Mission DesignMission-critical FanetMission-critical SystemNetwork Topology
In recent years, the emergence of flying ad hoc networks (FANETs) with multiple unmanned aerial vehicles (UAVs) has made it possible to effectively perform not only the far-off missions but also assorted complex missions. In this article, we consider a mission-critical FANET to perform given missions using multiple UAVs, taking into account a dynamic environment with a time-varying network topology. To effectively operate the mission-critical FANET, we study the joint mission assignment and topology management problem aiming at maximizing the weighted sum of mission and network performances, while guaranteeing end-to-end communications between mission-performing UAVs and their corresponding ground control stations, inter-UAV safety distance maintenance, and other mission-related constraints. To address this problem, we first develop three algorithms: one is to construct a mission-critical FANET from scratch, and the others are to manage the network topology and to switch UAV roles between mission performing and data relaying in response to the changes in the network topology. Then, we develop a dynamic mission-critical FANET operation algorithm incorporating the three algorithms with a few rules, by which the mission-critical FANET can be effectively managed and operated with reasonable computational complexity in the dynamic environment. Through simulation results, we show that our proposed algorithm works well in the dynamic environment while satisfying the constraints, and that its performance is not only superior to the existing algorithms but also close to the optimal performance.
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