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FREDI

model1 events
papersTODAY 04:00 UTC

FREDI Framework Targets Fair Resource Allocation for Dual-Threshold Edge Inference

A new arXiv paper introduces FREDI, a security-focused wireless edge-intelligence framework for event-triggered inference across user devices, edge servers, and the cloud. It combines proportional-fair resource allocation with a dual-threshold early-exit scheme so that each user device can partially process inference locally before offloading. The work aims to balance fairness, latency, and efficiency in cooperative multi-layer edge deployments.

edge-computing/resource-allocation/arxiv/inference