/high-order-tomography

Routing matrix inference with multivariate cumulants.

Primary LanguagePython

High-Order Tomography

High-Order Tomography (HOT) is a prototype tool for inferring routing matrices from end-to-end data. This repository is the official code for Topology Inference with Multivariate Cumulants: The Möbius Inference Algorithm, to appear in IEEE / ACM Transactions on Networking. Documentation for the code is under development at https://high-order-tomography.readthedocs.io/en/latest/.

Please note this is not quite a stable release. While the core algorithms are not expected to change, I am still ironing out the API and documentation.

License, Citation, and Acknowledgements

This project by Kevin D. Smith is licensed under a non-commercial Creative Commons license (CC BY-NC 4.0). When possible, please cite our paper:

@article{KDS-SJ-FB-AS:22,
  author = {K. D. Smith and S. Jafarpour and A. Swami and F. Bullo},
  title = {Topology Inference with Multivariate Cumulants: {The} {M\"obius} Inference Algorithm},
  journal = {IEEE/ACM Transactions on Networking},
  year = 2022,
  note = {To appear},
  url  {https://arxiv.org/pdf/2005.07880.pdf}
}

This work was supported by the U.S. Defense Threat Reduction Agency, under grant HDTRA1-19-1-0017.