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https://github.com/gh0st42/PONS
The Python Opportunistic Network Simulator. Run DTN simulations using SimPy.
https://github.com/gh0st42/PONS
Last synced: 29 days ago
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The Python Opportunistic Network Simulator. Run DTN simulations using SimPy.
- Host: GitHub
- URL: https://github.com/gh0st42/PONS
- Owner: gh0st42
- License: mit
- Created: 2023-04-28T10:48:35.000Z (over 1 year ago)
- Default Branch: master
- Last Pushed: 2024-11-09T20:19:36.000Z (about 1 month ago)
- Last Synced: 2024-11-09T21:17:06.618Z (about 1 month ago)
- Language: Jupyter Notebook
- Size: 4.99 MB
- Stars: 6
- Watchers: 2
- Forks: 3
- Open Issues: 3
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
- awesome-dtn - PONS - The Python Opportunistic Network Simulator. Run DTN simulations using SimPy. (DTN Simulations)
README
PONS - Python Opportunistic Network Simulator
===
A modular DTN simulator in the style of [the ONE](https://github.com/akeranen/the-one).
Features:
- distance- or contact-window-based network simulation
- DTN routing algorithms
- epidemic
- spray & wait
- first contact
- direct delivery
- PRoPHET
- static
- mobility
- random waypoint
- external ONE movement
- external ns2 movement
- contact plan connectivity model
- ION DTN contact plans
- [core contact plan}(https://github.com/gh0st42/ccm/)
- static networkx topology
- optionally: from graphml
- optionally: fluctuating from contact plan
- simulated user applications
- tools
- `netedit` for generating graphml topologies
- `ponsanim` for generating animated gifs and mp4 from graphml topologies with a contact plan or event logs
## Requirements
- simpy >= 4.0
- networkx >= 3.2
- plotting:
- seaborn
- pandas
- matplotlib
- numpy
- tools:
- pillow
- opencv-python
- tkinter
## Example
```python
import random
import json
import pons
import pons.routing
RANDOM_SEED = 42
SIM_TIME = 3600*24
NET_RANGE = 50
NUM_NODES = 10
WORLD_SIZE = (3000, 3000)
# Setup and start the simulation
random.seed(RANDOM_SEED)
moves = pons.generate_randomwaypoint_movement(
SIM_TIME, NUM_NODES, WORLD_SIZE[0], WORLD_SIZE[1], max_pause=60.0)
net = pons.NetworkSettings("NET1", range=NET_RANGE)
epidemic = pons.routing.EpidemicRouter()
nodes = pons.generate_nodes(NUM_NODES, net=[net], router=epidemic)
config = {"movement_logger": False, "peers_logger": False, "event_logger": True}
msggenconfig = {"type": "single", "interval": 30,
"src": (0, NUM_NODES), "dst": (0, NUM_NODES),
"size": 100, "id": "M"}
netsim = pons.NetSim(SIM_TIME, WORLD_SIZE, nodes, moves,
config=config, msggens=[msggenconfig])
netsim.setup()
netsim.run()
# print results
print(json.dumps(netsim.net_stats, indent=4))
print(json.dumps(netsim.routing_stats, indent=4))
```
Run using `python3` or for improved performance use `pypy3`.
## Magic ENV Variables
Some of the simulation core functions can be set during runtime without having to change your simulation code.
- `LOG_FILE` can be set to change the default event log file from `/tmp/events.log` to something else
- `SIM_DURATION` can be used to override the calculated simulation duration
For `netedit` there are also ways to influence its behavior:
- `BG_IMG` can be set to any image and it while be rendered as a background behind the network topology