Author

Lan-Pei Li

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Open access Sep 2026

On-board efficiency: comparing compressed deep learning and classical models for Earth observation

On-board processing is emerging as a key enabler for Earth observation (EO) missions, reducing downlink requirements and supporting more autonomous, event-driven operations. Deep convolutional neural networks (CNNs) deliver state-of-the-art performance on many EO tasks, but their memory footprint and computational dema...

G. Di Palma, Alessio Pardini, Lan-Pei Li et al. · Pattern Analysis and Applica... · 0 citations

Preprint Sep 2026

ContinuumBench: Benchmarking Joint Autoscaling and Placement Across Evaluation Regimes in the Cloud-Edge Continuum

Cloud-edge controllers coordinate service placement, replica scaling, and resource pre-warming to keep end-to-end latency within application deadlines. But evaluations often obscure the source of a reported gain: placement and scaling are studied separately; workload, connectivity, and calibration assumptions remain im...

Lan-Pei Li, Antonino Vaccarella, Vincenzo Lomonaco et al. · 0 citations

#artificial intelligence Preprint Sep 2026

Smart Adaptive Computing Across the Continuum: LLMs in IoT-Edge-Cloud Resource Management

Managing resources across IoT, edge, and cloud layers calls for continuous, context-aware decisions under constraints that rarely stay fixed. Deep reinforcement learning (DRL) handles this class of problems well, and large language models (LLMs) are increasingly used to augment DRL pipelines, yet the architectural rela...

Antonino Vaccarella, Lan-Pei Li, Vincenzo Lomonaco et al. · 0 citations