Turns power traces captured from an embedded SoC into an approximate weight matrix that initialises a new model when the original model and its training data are out of reach.
Compares vertical, horizontal, and data partitioning of CNNs across edge devices against an eavesdropper who reconstructs the input image from intercepted intermediate data.
Shows that the weights stored in an analog in-memory computing tile can be recovered from the power consumption of its ADCs, using a Transformer and an input-controlled weight-isolation technique.
Reinforcement learning assigns primary and backup copies of real-time tasks to fog nodes, balancing communication delay against the workload on each device.
Aging-aware task replication that keeps periodic hard real-time tasks at their reliability target over a multicore system’s lifetime while limiting the temperature that accelerates aging.
Passive primary/backup scheduling on heterogeneous multicores that mixes task mapping across core types and runs backups after primaries to remove execution overlap.