Iris is a system to coordinate complex network measurements from multiple vantage points. Think of it as a project similar to CAIDA Ark or RIPE Atlas, with the following features:
- Fully open-source code.
- Handle multi-round measurements, such as diamond-miner IP tracing measurements.
- Handle both centralized computation on a powerful server, and distributed probing on smaller agents.
- Can tolerate the temporary loss of agents, database or control-plane components.
We offer a public instance of Iris, as well as public measurement data, on iris.dioptra.io.
Please refer to the documentation for more information on how to use Iris, deploy your own instance and contribute to the project.
@article{10.1145/3523230.3523232,
author = {Gouel, Matthieu and Vermeulen, Kevin and Mouchet, Maxime and Rohrer, Justin P. and Fourmaux, Olivier and Friedman, Timur},
title = {Zeph & Iris Map the Internet: A Resilient Reinforcement Learning Approach to Distributed IP Route Tracing},
year = {2022},
issue_date = {January 2022},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
volume = {52},
number = {1},
issn = {0146-4833},
url = {https://doi.org/10.1145/3523230.3523232},
doi = {10.1145/3523230.3523232},
journal = {SIGCOMM Comput. Commun. Rev.},
month = {mar},
pages = {2–9},
numpages = {8},
keywords = {active internet measurements, internet topology}
}Iris is developed and maintained by the Dioptra group at Sorbonne Université in Paris, France.