ns3_sumo
An NS3+SUMO integrated orchestration of V2X networks for QoS Sustainability prediction
Science Score: 26.0%
This score indicates how likely this project is to be science-related based on various indicators:
-
○CITATION.cff file
-
✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
○DOI references
-
○Academic publication links
-
○Academic email domains
-
○Institutional organization owner
-
○JOSS paper metadata
-
○Scientific vocabulary similarity
Low similarity (9.8%) to scientific vocabulary
Repository
An NS3+SUMO integrated orchestration of V2X networks for QoS Sustainability prediction
Basic Info
- Host: GitHub
- Owner: anthonyKiggundu
- License: mit
- Language: C++
- Default Branch: master
- Size: 138 KB
Statistics
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
- Releases: 0
Metadata Files
README.md
Get Started
ns3+SUMO integration and functionality customization for QoS Sustainability datasets generation in V2X/UE networks
Dependencies - Compiled using gcc version 9.4.0 - On ubuntu1~20.04.2
With these extensions to NS-3 functionality, it is now possible to simulate mobility use-cases like V2X setups. The mobility profile for each device in a selected cite is topographically captured by Open Street Map and emulated using the SUMO tool. The output of this emulation is then fed into the TraCI library to record the devices' trajectories as a text file. An arbitrarily pre-defined file constituent of the base station locations plus this trajectories file are then the input to the NS-3 tooling such that the throughput measures of each device plus the standard connectivity metrics are written as a dataset for self-organizing the Radio Access Network using ML algorithms.
- A brief guide on getting the topographic city map captured using osm can be followed here.
- The output from osmWebWizard.py above is an osmsumo.cfg file from which trajectories are read (using TraCI) by the scratch/binder.py file.
- The trajectories are stored in the trajectories.txt and gNodeB poses in the scratch/enbs.txt
- All enhancements were done in the scratch/overly.cc file
- The metrics like distance between eNB and UE, how many UEs are attached to an eNB are recorded into a .csv file using the metricwriter.py_ file.
Notes
Contact - For pull requests please send an email to:
Acknowledgements - This work was done under the auspice of the AINET-ANTILLAS Project.
Citations
- Please use the Cite this repository link on the right pane in case you if you intend to cite the tooling for experimental use-cases.
License
ToDo - Extensions for compatibility to NR-LENA - Code refactoring
Owner
- Name: Anthony Kiggundu
- Login: anthonyKiggundu
- Kind: user
- Repositories: 2
- Profile: https://github.com/anthonyKiggundu