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[2602.20924] Airavat: An Agentic Framework for Internet Measurement
Summary
Airavat introduces an innovative framework for automating Internet measurement workflows, ensuring both generation and verification against established methodologies.
Why It Matters
As Internet measurement becomes increasingly complex, Airavat addresses the need for democratizing access to measurement tools. By automating workflow generation and validation, it enhances the reliability and accuracy of Internet measurements, making it easier for researchers and practitioners to conduct effective analyses.
Key Takeaways
- Airavat automates the generation of Internet measurement workflows.
- The framework includes verification and validation engines to ensure methodological correctness.
- Case studies demonstrate Airavat's ability to produce expert-level solutions and identify flaws in standard testing.
Computer Science > Networking and Internet Architecture arXiv:2602.20924 (cs) [Submitted on 24 Feb 2026] Title:Airavat: An Agentic Framework for Internet Measurement Authors:Alagappan Ramanathan, Eunju Kang, Dongsu Han, Sangeetha Abdu Jyothi View a PDF of the paper titled Airavat: An Agentic Framework for Internet Measurement, by Alagappan Ramanathan and 3 other authors View PDF HTML (experimental) Abstract:Internet measurement faces twin challenges: complex analyses require expert-level orchestration of tools, yet even syntactically correct implementations can have methodological flaws and can be difficult to verify. Democratizing measurement capabilities thus demands automating both workflow generation and verification against methodological standards established through decades of research. We present Airavat, the first agentic framework for Internet measurement workflow generation with systematic verification and validation. Airavat coordinates a set of agents mirroring expert reasoning: three agents handle problem decomposition, solution design, and code implementation, with assistance from a registry of existing tools. Two specialized engines ensure methodological correctness: a Verification Engine evaluates workflows against a knowledge graph encoding five decades of measurement research, while a Validation Engine identifies appropriate validation techniques grounded in established methodologies. Through four Internet measurement case studies, we demonstrate that Ai...