Our model offers an efficient solution to facilitate the data exchange between ns-3 and Python-based AI frameworks. It does not implement any specific AI algorithms. Instead, it focuses on enabling interconnectivity between Python and C++.

use ns-3 to generate training data. > Ns-3 is open source AI/ML algorithms. Actions: parameters, prediction... Data: observation, states... Offline training: The model is first trained with offline data (from real world or ns-3). Two ways to use the model in the network/simulation.

Real-time Interaction between Solver and ns-3. Create Offline Simulation Replicating Solver Output. Dynamic Simulations Based on Solver Output. − Accurate, repeatable and reproducible − Propagation loss, channel occupancy, rate adaptation, MIMO, ... E. N. Almeida et al.,

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. Examples. In current release, we provide two examples for test.

2020年6月17日 · In this paper, we propose a newly designed module between ns-3 and multiple Python-based AI frameworks, namely ns3-ai, to provide efficient and high-speed data exchange between the AI engines and ns-3.

2023年9月7日 · The objective of this proposed project is to enhance the ns3-ai module, which facilitates the connection between ns-3 and Python-based ML frameworks using shared memory. The main focus of this enhancement is to optimize performance and improve usability.

ns–3 is widely recognized as an excellent open-source networking simulation tool utilized in network research and education. In recent times, there has been a growing interest in integrating AI algorithms into network research, with many researchers opting for open-source frameworks such as TensorFlow and PyTorch.

2020年6月17日 · In this paper, we present ns3-ai, a newly designed module between ns-3 and multiple Python-based AI frameworks, to provide efficient and high-speed data exchange between AI algorithms and ns-3.

In this paper, we present ns3-ai, a newly designed module between ns-3 and multiple Python-based AI frameworks, to provide efi-cient and high-speed data exchange between AI algorithms and ns-3.

Our model offers an efficient solution to facilitate the data exchange between ns-3 and Python-based AI frameworks. It does not implement any specific AI algorithms. Instead, it focuses on enabling interconnectivity between Python and C++.