Key Achievements
Developed a dynamic cluster-based hierarchical routing framework achieving 81% faster query resolution and 76.6% fewer nodes visited compared to Dijkstra’s algorithm.
Reduced memory usage by 4× (5 GB vs. 21 GB) and maintained 89% cluster stability during network topology changes.
Lowered cluster recomputation overhead by 72%, enabling scalability to 20M+ nodes in large dynamic networks.
Balanced efficiency with adaptability, maintaining ≤18% path length deviation while supporting real-time network changes.
->Used Python library for simulation purpose of different dynamic network routing algorithm.