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[OFC 2021] BOW: First Real-World Demonstration of a Bayesian Optimization System for Wavelength Reconfiguration

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BOW: Bayesian-Optimized Wavelengths

1. Overview

BOW is a bayesian optimization system that optimizes optical wavelengths' Quality of Transmission (QoT) metrics (e.g., OSNR) for wavelength reconfigurations. BOW is built on Python 3.8.8, with Ax (https://ax.dev) as the Bayesian Optimization backend, GNPy (https://gnpy.readthedocs.io/en/master/) as the optical-layer QoT estimator, and FCR (https://github.com/facebookincubator/FCR) as the control interface to optical network devices.

For a full technical description on BOW, please read our OFC 2021 paper:

Z. Zhong, M. Ghobadi, M. Balandat, S. Katti, A. Kazerouni, J. Leach, M. McKillop, Y. Zhang, "BOW: First Real-World Demonstration of a Bayesian Optimization System for Wavelength Reconfiguration," OFC, 2021. http://bow.csail.mit.edu/files/OFC-21-BOW-final.pdf

For more details on BOW, please visit our website: http://bow.csail.mit.edu

2. Requirement

  • Python 3.8
  • Ax 0.1.20
  • GNPy 2.1

3. License

BOW is MIT-licensed.