Python-based-SDN-simulation-with-dynamic-path-recovery-explained-step-by-step-

Python-based SDN simulation with dynamic path recovery explained step-by-step using Jupyter Notebook. Ideal for students and researchers.

📡 SDN Path Recovery Simulation in Python

This repository presents an educational and research-focused simulation of Software-Defined Networking (SDN), implemented in Python using Jupyter Notebook. The simulation emphasizes path recovery mechanisms under failure scenarios, suitable for academic use, network analysis, and teaching.

📽️ Related Tutorial Video:
Watch the walkthrough of the notebook with technical explanations on YouTube:
▶️ Simulate SDN with Python | Path Recovery Explained

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🧠 Project Objectives

• To simulate a simplified SDN environment using Python
• To model link/node failure events and analyze their effects
• To implement and observe path recovery logic dynamically
• To support education and research in programmable network design

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🧪 Contents

• SDN_path_recovery_and_simulation_break_down.ipynb
  A detailed, self-contained notebook covering:
  • SDN architecture overview
  • Network topology creation
  • Flow installation and traffic handling
  • Failure simulation and recovery logic

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🛠️ Tools & Frameworks

• Python 3.x
• Jupyter Notebook
• (Optional) Mininet and Ryu Controller for practical integration

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⚙️ How to Use

1. Clone the repository:

   git clone https://github.com/your-username/sdn-path-recovery-python.git
   cd sdn-path-recovery-python

2. Launch the notebook:

   jupyter notebook

3. Open and run the .ipynb file step-by-step.

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🎓 Recommended For

• Graduate and undergraduate students studying SDN or networking
• Researchers prototyping failure handling algorithms
• Educators seeking illustrative SDN lab material
• Developers exploring SDN logic and traffic management