ns-3 Scaling for Next G Wireless Networks

The University of Washington has received an NSF CCRI Award (PI Prof. Sumit Roy) to improve the scalability of ns-3’s wireless simulation models and scenarios.  This award started in Fall 2020 and is part of a collaborative research program with Georgia Tech.

• Research Objectives:
  • Efficient Link-2-System (L2S) mappings for runtime-efficient wireless error models
    • Sian Jin published advances on this topic, presented at the Workshop on ns-3
  • Enhanced Cross-Layer and Abstraction Approaches
    • Shepherd the Sandia National Laboratories kmsim implementation to the ns-3 mainline
  • • Develop cellular wraparound techniques (e.g. sample techniques) for ns-3
  • Network Simulation Parallelization
    • Georgia Tech. is leading this thrust
• Educational/Outreach Objectives
  • Training and tutorials
    • April 2021: 5G New Radio with ns-3, (Tom Henderson, co-authored with Lorenza Giupponi, CTTC)
    • June 2021: Machine Learning in ns-3: ns3-ai module, Introduction and Hands-on Example, Hao Yin, co-authored with Pengyu Liu (Huazhong University of Science and Technology)
    • June 2021: How to contribute code to ns-3, Tom Henderson
    • June 2021: Efficient PHY Layer Abstraction in ns-3: Principles and Implementation, Sian Jin and Tom Henderson
    • Improved example programs are planned for development
  • Educational materials
    • To be developed
  • Software maintenance
    • During this award period, Tom Henderson has organized and published six
      releases (ns-3.33 through ns-3.38) of the open source project.