BROWSE
Detail
Conference Paper
NetSimGym: The Gymnasium for Reinforcement Learning in Networking Research
Cited 1 time in 
Share 
Share
- Authors
- Inho Cha, Seungjae Shin, Kihoon Kim, Yerin Ahn, Taeyeon Kim, Sangheon Pack
- Issue Date
- 2025-06
- Citation
- European Conference on Networks and Communications (EuCNC) 2025, pp.339-344
- Language
- English
- Type
- Conference Paper
- Abstract
- Gymnasium (Gym) is a de facto framework for building a target environment of reinforcement learning (RL)- based control and optimization. Therefore, there are several efforts to interwork existing network simulators (e.g., ns-3) with Gym for RL-based networking research. In an effort to provide a new alternative RL playground for networking research, we developed NetSimGym, a wrapper framework that interconnects NetSim, which provides rich and convenient features for network simulations, and Gym. NetSimGym provides a set of core functions to exchange observation, reward, action, and related information between Gym and NetSim through the Protocol Buffers (protobuf)-based messaging interface. This enables NetSim users to easily integrate various RL algorithms with NetSim without needing to implement a data exchange and synchronization mechanism. We open the source code of NetSimGym under the Massachusetts Institute of Technology (MIT) license and expect it to be useful to NetSim users who want to adopt RL in research and development.
- KSP Keywords
- Core Functions, Data exchange, NS-3, Network Simulation, Network Simulator(NS2), Reinforcement learning(RL), Source Code, Synchronization Mechanism, protocol buffers, research and development(R&D), target environment