Areesha Raza@AreeshaRaza

Ensuring optimal network performance and efficient bandwidth allocation in modern digital infrastructures is crucial, especially in educational institutions where multiple nodes compete for resources. This project introduces a Smart Network Resource Allocation System that leverages Software-Defined Networking (SDN), machine learning, and time-series forecasting to distribute bandwidth intelligently among different schools. The system gathers real-time bandwidth usage data, detects anomalies using the Interquartile Range (IQR) method, and predicts future demand through the Prophet time-series forecasting model. The allocated bandwidth is optimized based on these predictions, ensuring fair and efficient distribution among schools. The SDN-based load balancer also computes energy-efficient network routes to reduce congestion and enhance data flow efficiency. The solution provides a Streamlit-based interactive dashboard, allowing users to visualize bandwidth trends, monitor real-time allocations, and review detected anomalies. This approach ensures proactive network management, preventing bottlenecks and improving overall network performance.