Currently, more and more researchers are willing to apply AI algorithms to network research. Most AI algorithms are likely to rely on open source frameworks such as TensorFlow and PyTorch, but these frameworks are developed independently of ns-3 and extremely hard to merge, so it is more reasonable and convenient to connect them with data interaction. This ns-3 extension module provides a high-efficiency solution to enable the data interaction between ns-3 and other python based AI frameworks.
Inspired by ns3-gym, but using a different approach (shared memory) which is faster and more flexible.
In current release, we provide two examples for test. To run them without depending on the AI frameworks' environment, we provide python scripts only exchanging data. For details, please check here .
This work is designed and finished by Dian Group in Huazhong University of Science and Technology.
Works with ns-3.30Build History : ns3-ai v1.0.0