SEM-O-RAN

Code repository to reproduce the results of our papers "SEM-O-RAN: Semantic and Flexible O-RAN Slicing for NextG Edge-Assisted Mobile Systems", presented at IEEE INFOCOM 2023, and "SEM-O-RAN: Semantic O-RAN Slicing for Mobile Edge Offloading of Computer Vision Tasks", published in IEEE Transactions on Mobile Computing in 2023.

Content

This repository contains the following files:

• LICENSE

  This file contains the license covering the software and associated documentation files provided in this repository.

• README.md

  This is the file that contains the instructions to use the provided software that you are currently reading.

• example.m

  This MATLAB script is an example of how to use the SF-ESP solver.

• example_live.mlx

  The same as above, but as a MATLAB Live Script for easier interaction.

• greedy_knapsack.m

  A MATLAB function that implements a knapsack problem solver, which is used as a baseline competitor of SEM-O-RAN in the provided example.

• semoran.m

  This is the MATLAB function that implements the solver of the Semantic Flexible Edge Slicing Problem (SF-ESP).

Instructions

To test our code, clone this repository using the following command:

git clone https://github.com/corrado113/Semoran.git

Then, run with MATLAB example_live.mlx or example.m.

Cite us

If you have used our work in your research, please consider citing our paper:

@article{puligheddu2022sem,
  author={Puligheddu, Corrado and Ashdown, Jonathan and Chiasserini, Carla Fabiana and Restuccia, Francesco},
  journal={IEEE Transactions on Mobile Computing}, 
  title={SEM-O-RAN: Semantic O-RAN Slicing for Mobile Edge Offloading of Computer Vision Tasks}, 
  year={2023},
  volume={},
  number={},
  pages={1-16},
  doi={10.1109/TMC.2023.3339056}}

Changelog

• 18/12/2023
  • Our work has been accepted in IEEE Transactions on Mobile Computing
    • Change the README introduction
    • Update the article reference in the README with our recently accepted journal paper
• 01/03/2023
  • Upload of new files in the repository:
    • the SEM-O-RAN solver matlab function
    • a baseline knapsack problem solver
    • two example files to test SEM-O-RAN and compare it with a baseline competitor
  • Extension of the README.md file, which now contains:
    • the content list of the repository
    • instructions on how to use the provided code
    • the reference to the SEM-O-RAN paper preprint