AEGIS introduces risk-budgeted online scheduling with LSTM prediction and game-theoretic allocation to improve timely inference ratios and reduce violation bursts in continuous edge computing.
Resource allocation for video diffusion task offloading in cloud-edge networks: A deep active inference approach
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Risk-Budgeted Online Scheduling for Continuous Edge Inference over Evolving Time Horizons
AEGIS introduces risk-budgeted online scheduling with LSTM prediction and game-theoretic allocation to improve timely inference ratios and reduce violation bursts in continuous edge computing.