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cloud-computing

topic3 events
papersSEP 11 04:00 UTC

mmFHE Runs Whole mmWave Sensing Pipeline Under Homomorphic Encryption

A new arXiv paper introduces mmFHE, a system that performs an entire cloud-side mmWave sensing workflow, including signal processing and machine learning inference, on encrypted data using fully homomorphic encryption. Range profiles are encrypted on the edge device first, so the cloud never sees raw sensing data. The work aims to enable privacy-preserving sensing services without giving up cloud compute.

privacy/homomorphic-encryption/mmwave/research
papersSEP 10 04:00 UTC

LLMs combine with deep reinforcement learning for IoT-edge-cloud resource management

A new arXiv paper surveys how large language models can support deep reinforcement learning in managing resources across IoT, edge, and cloud layers. The work focuses on continuous, context-aware decision-making in environments where constraints shift constantly. It positions LLMs as a complement to established DRL techniques for adaptive computing across the computing continuum.

llms/reinforcement-learning/edge-computing/iot