Federated Learning Architecture¶
Scaffold
This MicroSim has been scaffolded from its specification. The interactive implementation has not been built yet.
Learning Objective¶
TBD
- Bloom Level: TBD
- Bloom Verb: TBD
- Library: p5.js
Preview¶
Specification¶
The full specification below is extracted from Chapter 18: Advanced Data, Emerging AI, and Autonomous Architectures.
Type: Interactive simulation
**sim-id:** federated-learning-explorer<br/>
**Library:** p5.js<br/>
**Status:** Specified
**Purpose:** Animated visualization of the federated learning training loop showing model distribution, local training, gradient aggregation, and model improvement across rounds.
**Components:**
- Central coordinator (hub)
- 6 participating nodes (hospitals, devices, banks) with simulated local datasets
- Communication channel animations
**Controls:**
- Privacy budget slider (differential privacy ε): 0.1–10 (lower = more privacy, more noise)
- Non-IID heterogeneity slider: low–high (more heterogeneity = slower convergence)
- Number of rounds slider: 1–100
- Fraction of nodes per round: 0.2–1.0
**Display:**
- Animated model update flows (compression level visualization)
- Convergence curve: global model accuracy vs. rounds
- Privacy-utility tradeoff chart
- "Model leakage risk" indicator based on privacy budget