A graph attention diffusion-based solution generator is shown to produce near-optimal offloading and resource allocation decisions across synthetic low-altitude MEC instances, outperforming random, alternating, graph-RL, and graph diffusion baselines.
Joint Resource Management for Energy-efficient UA V- Assisted SWIPT-MEC: A Deep Reinforcement Learning Approach,
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Joint Task Offloading and Resource Allocation in Low-Altitude MEC via Graph Attention Diffusion
A graph attention diffusion-based solution generator is shown to produce near-optimal offloading and resource allocation decisions across synthetic low-altitude MEC instances, outperforming random, alternating, graph-RL, and graph diffusion baselines.