Pramana: A Composable Backend for Empirical Networking Research
A new paper on arXiv (2607.26352) introduces Pramana, a composable, domain-specific backend designed to accelerate empirical networking research by reducing the lag between hypothesis formation and data generation. The authors argue that current overhead is high, often requiring researchers to start from scratch for each new idea, and that this gap will worsen with AI-assisted ideation. Pramana is envisioned as a thin waist architecture to bridge this gap. The paper explores how to enable faster validation of networking hypotheses, such as testing whether bulk BBR download shares a bottleneck fairly with Google Meet traffic.
Key facts
- Paper titled 'Pramana: A Composable, Domain-Specific Backend for Empirical Networking Research'
- Published on arXiv with ID 2607.26352
- Announce type: cross
- Pramana is a composable, domain-specific backend
- Designed to reduce lag between ideation and data generation
- Highlights example: testing BBR download vs Google Meet traffic
- Argues current overhead forces researchers to start from scratch
- Warns gap will worsen in agentic AI era
Entities
Institutions
- arXiv