Rumba: Difference between revisions
Jump to navigation
Jump to search
(Created page with "{{Under construction}}") |
No edit summary |
||
Line 1: | Line 1: | ||
{{Under construction}} | {{Under construction}} | ||
Rumba is a Python framework for setting up Ouroboros (and RINA) networks in a test environment that was originally developed during the ARCFIRE project. Its main objectives are to configure networks and to evaluate a bit the impact of the architecture on configuration management and devops in computer and telecommunications networks. The original Rumba project page is [https://gitlab.com/ARCFIRE/Rumba here]. | |||
Rumba can quickly set up test networks for Ouroboros that are made up of many IPCPs and layers. I try to keep it up-to-date for the Ouroboros prototype. | |||
The features of Rumba are: | |||
easily define network topologies | |||
use different prototypes]: | |||
Ouroboros1 | |||
rlite | |||
IRATI | |||
create these networks using different possible environments: | |||
local PC (Ouroboros only) | |||
docker container | |||
virtual machine (qemu) | |||
jFed testbeds | |||
script experiments | |||
rudimentary support for drawing these networks (using pydot) |
Revision as of 20:24, 7 June 2022
This page is under construction
Rumba is a Python framework for setting up Ouroboros (and RINA) networks in a test environment that was originally developed during the ARCFIRE project. Its main objectives are to configure networks and to evaluate a bit the impact of the architecture on configuration management and devops in computer and telecommunications networks. The original Rumba project page is here.
Rumba can quickly set up test networks for Ouroboros that are made up of many IPCPs and layers. I try to keep it up-to-date for the Ouroboros prototype.
The features of Rumba are:
easily define network topologies
use different prototypes]: Ouroboros1 rlite IRATI
create these networks using different possible environments: local PC (Ouroboros only) docker container virtual machine (qemu) jFed testbeds
script experiments
rudimentary support for drawing these networks (using pydot)