Inspiration
Many students find NS2 simulations difficult to interpret because of how bandwidth, queue sizes, delays, and CBR traffic interact. Manual analysis is time-consuming and often confusing. This project was inspired by the need for a tool that uses AI to simplify NS2 assignment explanations and help students learn networking concepts more efficiently.
What it does
Smart Assignment Solver – NS2 Bottleneck Analyzer takes an NS2 script and generates a structured explanation using an AI-driven workflow.
It identifies the following:
Bottleneck link
CBR flow behavior
Throughput and delay patterns
Packet losses
Fairness between flows
Recommended configuration fix
The final output is clean, formatted, and ready for academic submission.
How we built it
The project uses Perplexity Comet and a multi-agent workflow.
Agents used
Research Agent: Reads link bandwidth, delay, queue limits, and traffic details
Reasoning Agent: Determines congestion, fairness, and bottleneck behavior
Summarization Agent: Converts the technical analysis into clear explanations
Formatting Agent: Produces a clean structured output
The final result is exported into a PDF made entirely using Markdown-based formatted content.
Challenges we ran into
Understanding complex NS2 topologies and flow interactions
Explaining concepts such as tail-drop, queue buildup, and fairness in simple terms
Maintaining technical accuracy while keeping explanations beginner-friendly
Formatting the final analysis into a polished, professional document
Accomplishments that we're proud of
Successfully created a readable, technically correct NS2 bottleneck analysis
Generated a complete, submission-ready PDF using Markdown formatting
Built a reusable workflow for analyzing future NS2 scripts
Demonstrated how AI can simplify complex academic problems
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