Dynamic Routing Simulation

A Python project that simulates different routing algorithms on dynamic networks with visualization capabilities.

Features

• Dynamic network simulation with changing topology
• Multiple routing algorithms:
  • Dijkstra's algorithm
  • Floyd-Warshall algorithm
  • Q-learning reinforcement learning
  • Deep Q-learning neural networks
• Real-time visualization (PyQt6 backend)
• Performance metrics tracking
• Easy-to-use interface for all skill levels

Getting Started

For Non-Technical Users

1. Install Python:

   • Download from python.org
   • Check "Add Python to PATH" during installation

2. Run the Simulation:

   • Windows: Double-click run_simulation.bat
   • Mac/Linux: Run ./run_simulation.sh in terminal
   • Or simply: python main.py

For Developers

# Setup virtual environment (recommended)
python -m venv venv
source venv/bin/activate  # Linux/Mac
venv\Scripts\activate     # Windows

# Install dependencies
pip install -r requirements.txt

# Run test simulation
python test_simulation.py

# Run custom simulation
python main.py --nodes 20 --packets 100 --algorithm qlearning --visualize

Command Line Options

Parameter	Description	Default
--nodes	Number of nodes in network	10
--packets	Number of packets to simulate	100
--algorithm	Routing algorithm to use	dijkstra
--visualize	Enable real-time visualization	Off
--max_steps	Maximum simulation steps	1000

Available algorithms: dijkstra, floyd, qlearning, deepq

Output Files

• network_final.png: Final visualization screenshot
• network_step_*.png: Step-by-step screenshots (if visualization fails)

Troubleshooting

1. Visualization Issues:

   • Try simpler test: python test_simulation.py
   • Check console for error messages
   • Screenshots are saved as fallback

2. Missing Packages:

   pip install -r requirements.txt

3. Need Help?
   Contact: [Your Email/Contact Info]

Project Structure

├── network_simulation/    # Core simulation logic
├── routing_algorithms/    # Pathfinding implementations  
├── reinforcement_learning/ # RL algorithms
├── visualization/         # PyQt6 visualization
├── main.py                # Main entry point
├── test_simulation.py     # Test script
├── run_simulation.*       # Platform-specific run scripts
└── requirements.txt       # Dependencies

License

MIT License