Open Source
Open projects for networking technologies and developer tools
Technologies in Focus
Our Projects
Open educational materials and tools for studying network protocols. Designed for bachelor and master students, PhD researchers, and network technology developers
quic-test
v2.0.0 Active Integrated 6 Comprehensive platform for testing and analyzing network protocols: QUIC, MASQUE, ICE/STUN/TURN with professional TUI visualization. Includes real-time monitoring, network simulation, security testing, and cloud integration.
quic-test
v2.0.0 Active IntegratedComprehensive platform for testing and analyzing network protocols: QUIC, MASQUE, ICE/STUN/TURN with professional TUI visualization. Includes real-time monitoring, network simulation, security testing, and cloud integration.
Comprehensive platform for testing and analyzing network protocols: QUIC, MASQUE, ICE/STUN/TURN with professional TUI visualization. Includes real-time monitoring, network simulation, security testing, and cloud integration.
Starred by
License: Apache 2.0
Technologies
Key Features
- BBRv2/BBRv3
- QUIC Bottom TUI
- Network Simulation
- Security Testing
- Cloud Deployment
- TCP-over-QUIC Research
AI Routing Lab
v2.0.0 Active Integrated 1 1 Research project for predictive route selection using machine learning. Achieves >92% accuracy in predicting latency and jitter for route optimization in CloudBridge network infrastructure.
AI Routing Lab
v2.0.0 Active IntegratedResearch project for predictive route selection using machine learning. Achieves >92% accuracy in predicting latency and jitter for route optimization in CloudBridge network infrastructure.
Research project for predictive route selection using machine learning. Achieves >92% accuracy in predicting latency and jitter for route optimization in CloudBridge network infrastructure.
Starred by
License: MIT
Technologies
Key Features
- Latency Prediction
- Jitter Prediction
- Route Selection Optimization
- ML Model Training
- Real-time Inference
MASQUE VPN
v2.0.0 Active 66 7 VPN implementation based on MASQUE (CONNECT-IP) protocol using QUIC transport. Enhanced by CloudBridge Research Center for use in educational initiatives for MPEI students and network technology researchers. Includes web management interface, mutual TLS authentication, and Prometheus metrics support.
MASQUE VPN
v2.0.0 ActiveVPN implementation based on MASQUE (CONNECT-IP) protocol using QUIC transport. Enhanced by CloudBridge Research Center for use in educational initiatives for MPEI students and network technology researchers. Includes web management interface, mutual TLS authentication, and Prometheus metrics support.
VPN implementation based on MASQUE (CONNECT-IP) protocol using QUIC transport. Enhanced by CloudBridge Research Center for use in educational initiatives for MPEI students and network technology researchers. Includes web management interface, mutual TLS authentication, and Prometheus metrics support.
Starred by
License: MIT
Technologies
Key Features
- MASQUE CONNECT-IP
- Mutual TLS Authentication
- Web Management UI
- Cross-Platform Support
- IP Pool Management
- Real-time Monitoring
- Prometheus Metrics
- High Performance (RWMutex)
- Multi-language UI (RU/EN/ZH)
Project Integration
Our projects work together to create comprehensive solutions
quic-test ↔ AI Routing Lab
Integration for intelligent routing
quic-test and AI Routing Lab work together to create a machine learning-powered intelligent routing system. quic-test generates network performance metrics (latency, jitter, packet loss) via Prometheus, which are collected by AI Routing Lab to train machine learning models. The trained models predict optimal routes with >92% accuracy, enabling CloudBridge Relay to select the best paths for traffic.
Data Flow
Key Benefits
- Latency prediction accuracy >92%
- Automatic route optimization based on real-time data
- Integration via standard protocols (Prometheus)
How to Contribute
We welcome contributions from all developers. Follow these guidelines when submitting a pull request
License
All projects are distributed under MIT or Apache 2.0 licenses. Please ensure you agree with license terms before contributing.
Pull Requests
Submit PRs to the appropriate repository. All PRs must include description, tests and documentation. We will review within 1-2 weeks.
Code Style
Follow existing code style and use standard formatting tools (gofmt for Go, rustfmt for Rust). All commits must be atomic.
Testing
Add tests for all new features. Minimum 80% coverage for critical code. Use unit and integration tests.
Documentation
Update README and documentation when adding features. All APIs must be well documented.
Discussion
For major changes, open an issue and discuss the design first. We value your feedback.
Let's Build Together
CloudBridge Research aims to build an active community of developers and researchers. Join us on GitHub, discuss ideas, and help improve our projects.