DESIGN AND SIMULATION OF NETWORK TRAFFIC SYSTEM ANALYSIS

The growing dependence on information and communication technology (ICT) within educational institutions has increased the demand for a reliable and efficient network infrastructure. This project outlines the design and simulation of a real-time network traffic analysis system specifically tailored for the ICT environment of institutions. The objective is to monitor, capture, and visualize traffic flows using both live network packets and simulated data, thereby equipping administrators with valuable insights for informed decision-making and performance optimization. The system leverages several open-source technologies: Scapy for packet sniffing and logging, Dash and Plotly for visualization, and Python for data processing and simulation logic. It operates in two modes—Live Capture and Simulated—allowing for flexibility in monitoring actual network behavior as well as assessing performance under controlled conditions. The dashboard features real-time charts that illustrate throughput trends and protocol distribution, enabling users to easily identify spikes, congestion, or unusual traffic patterns. Comprehensive evaluations were conducted, revealing varied traffic volumes during live captures with a predominant use of the TCP protocol, while simulated data showcased a balanced mix of TCP, UDP, and other protocols. These findings affirmed the system’s capability to manage different traffic environments and provide relevant analytics. This study concludes that implementing such a system can significantly enhance traffic management, security, and resource planning within academic networks. Furthermore, the project establishes a foundation for future advancements, including anomaly detection through machine learning, predictive analytics, mobile accessibility, and automated alerts. This work contributes meaningfully to the ongoing research aimed at improving network monitoring in educational settings.