Graphical Visualization of simulated ns3 data with Grafana

This example showcases graphical data visualization using Grafana. Data is extracted from a 5G ns3 simulation into csv files and sent to an InfluxDB server via Telegraf. Grafana then gathers data and plots it on a dashboard, allowing for easier analysis and interpretation. We created four dashboards to showcase all the data generated from "cu-up", "cu-cp" and "du" files within the simulation container. The forth dashboard plots aggregated data of interest.

Services and Ports

Grafana

URL: http://localhost:3000
User: admin
Password: admin

Telegraf

Port: 8125 UDP (StatsD input)

InfluxDB

Port: 8086 (HTTP API)
User: admin
Password: admin
Database: influx

How to run the project

Start the stack with docker compose

$ docker compose up

Open Grafana and select a dashboard

URL: http://localhost:3000
User: admin
Password: admin

Run the python script

$ docker compose exec ns3 /bin/bash
$ cd ns3-mmwave-oran
$ python3 sim_watcher.py

Run the ns3 simulation

$ docker compose exec ns3 /bin/bash
$ cd ns3-mmwave-oran
$ ./waf --run "scratch/scenario-zero.cc --enableE2FileLogging=1"

You may want to set the following options in the last command:

--RngRun=n, where n is a positive integer representing the seed for the pseudo-random number generator.
--simTime=x, where x is the simulation time (in seconds)

Usage

Once everything is running correctly make sure the absolute time range on Grafana is set to "Last 5 minutes" so that data will appear as soon as it is sent.
When data is visible you may want to change the absolute time range to:
From: timestamp of the first visible measurement
To: From timestamp + simulation time

License

The MIT License (MIT). Please see License File for more information.

Acknowledgements and credits

https://github.com/bcremer/docker-telegraf-influx-grafana-stack.git

pagmatt/docker-telegraf-influx-grafana-stack