HFL-Lite: Sparse Coding for Lightweight Hierarchical Federated Learning in Computation-Limited Sensor Networks
This work proposes HFL-Lite, a hierarchical federated learning framework that achieves practical privacy without cryptographic primitives, and shows that HFL-Lite reduces per-round communication to 0.5 KB and sensor-side latency to 9 ms while delivering competitive accuracy.