AI Routing Lab
Predictive route selection by latency/jitter using machine learning to achieve prediction accuracy >92%
Project Overview
AI Routing Lab is a research project focused on developing machine learning models for predictive route selection in CloudBridge network infrastructure. The project aims to achieve >92% accuracy in predicting latency and jitter for optimal route selection.
The project integrates with quic-test for model validation on real QUIC traffic and with CloudBridge Relay for real-time routing optimization.
Key Objectives
Accuracy >92%
Develop ML models for latency and jitter prediction with R² > 0.92 accuracy
Route Optimization
Real-time route selection optimization through integration with CloudBridge Relay
Current Status
Completed
- Created LatencyPredictor and JitterPredictor models with ensemble architecture (Random Forest + Gradient Boosting)
- Implemented RoutePredictionEnsemble for combining latency and jitter predictions
- Integrated FeatureExtractor from cloudbridge-ai-service for feature extraction
- Created laboratory framework for experiments
- Organized reports structure by year, month, and version
In Progress
- Integration with quic-test for metrics collection and validation
- Adapting time-series models (LSTM, ARIMA, Prophet) for latency prediction
- Developing API for CloudBridge Relay integration
Technical Details
Models
- • LatencyPredictor (Ensemble: RF + GB)
- • JitterPredictor (Ensemble: RF + GB)
- • RoutePredictionEnsemble
- • FeatureExtractor (Time, Statistical, Domain features)
Technologies
Performance Metrics
- • R² Score: >0.92 (target)
- • Inference Time: ~2ms per prediction
- • Throughput: 1000+ predictions/sec
- • Ensemble reduces variance by 15-25%
Model Accuracy Over Training Time
* Target accuracy: R² >92%, inference time <10ms
Model Comparison
* Ensemble architecture reduces variance by 15-25%
Development Status
- • Models Created: 3
- • Experiments Ready: 2
- • Version: 1.1
- • Status: Active Development
Project Documentation
Architecture
Guides
Development
Experiments & Reports
Related Projects & Technologies
Related Research
- Network Performance Lab
QUIC/MASQUE testing and optimization