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Mobility-disentangled federated continual graph learning for open-world intrusion detection in partitioned FANETsOpen-world intrusion detection in flying ad hoc networks (FANETs) is challenged by rapid three-dimensional mobility, evolving attack streams, non-IID local observations, intermittent participation,... Author: Hien Le Thi Thu Keyword: Flying ad hoc networks Mobility–attack disentanglement Open-world intrusion detection Federated continual graph learning Partition-aware knowledge fusion
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Mobility-Predictive Graph Neural Routing for Delay-Constrained FANETs in Dynamic 3D AirspaceRapid three-dimensional mobility in flying ad hoc networks (FANETs) causes routes selected from the current topology to become invalid before packets reach subsequent hops, particularly for flows with... Author: Ha Dien Thi Hong Keyword: FANET routing mobility prediction temporal graph neural network deadline-constrained routing uncertainty calibration
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Joint power control and spectrum access optimization in FANET via reinforcement learningThis paper studies joint power control and spectrum access in dynamic flying ad hoc networks (FANETs) under co-channel interference and adaptive jamming. We propose a graph neural network-aided... Author: Dung Nguyen Thi Keyword: FANET Multi-agent reinforcement learning Graph neural networks Anti-jamming Resource optimization
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Risk-sensitive spatio-temporal graph reinforcement learning for predictive and propulsion-aware routing in 6G-enabled FANETsFlying ad hoc networks (FANETs) in 6G environments require routing schemes that can cope with rapid topology changes, limited UAV energy resources, and unstable air-to-air links. This paper proposes a... Author: Nguyen Thu Thi Keyword: 6G-enabled FANETs Spatio temporal graph learning Risk sensitive deep reinforcement learning Propulsion aware routing Route survival probability
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