Upgrading the most widely used open source network simulator
Simulation of emerging next-generation wireless networks continues to be an invaluable component of the design, evaluation, and innovation cycle. However, the increasing complexity of wireless network simulation due to continual physical layer advances presents a fundamental challenge.
This project, a collaborative effort by the University of Washington and the Georgia Institute of Technology, will extend the popular ns-3 open-source network simulator to meet the challenges of modeling efficient yet accurate simulation-based, next-generation wireless 5G and beyond networks. The primary objective is to develop simulation methods that achieve, in the face of increasing complexity, the desired balance between maintaining simulation run-time efficiency, while preserving accuracy of measured network parameters like loss, throughput, and latency. This work will improve ns-3’s run-time scalability for dense, heterogeneous network scenarios, advancing the state-of-the-art in simulation performance for dense wireless networks that increasingly characterize many next-G scenarios of interest.
In addition, the project plans to improve ns-3 usability and further adoption through increased community outreach and creation of new educational material to lower barriers to entry for a new generation of ns-3 users.
Yuchen Liu, Shelby K. Crisp, and Douglas M. Blough. 2021. Performance study of statistical and deterministic channel models for mmWave wi-fi networks in ns-3. Proceedings of the Workshop on ns-3. Association for Computing Machinery, New York, NY, USA, 33–40. DOI: https://doi.org/10.1145/3460797.3460802
Sian Jin, Sumit Roy, and Thomas R. Henderson. 2021. EESM-log-AR: an efficient error model for OFDM MIMO systems over time-varying channels. Proceedings of the Workshop on ns-3. Association for Computing Machinery, New York, NY, USA, 17–24. DOI: https://doi.org/10.1145/3460797.3460800
Networks
National Science Foundation