Efficient Task Orchestration Including Mixed Reality Applications in a Combined Cloud-Edge Infrastructure
This repository contains all the experiments presented in the paper Efficient Task Orchestration Including Mixed Reality Applications in a Combined Cloud-Edge Infrastructure.
In this work, we propose a task orchestration solution that considers the hybrid Cloud/Edge infrastructure and generates a locally optimal solution through mathematical programming.
First of all, to run the experiments, we need to install the CPLEX optimization tool used in this implementation.
First download the IBM ILOG CPLEX Optimization Studio on the project website.
After downloading the binary, run the following command in the repository where the file is located:
bash <CPLEX_BINARY_FILE.bin>
It will be asked the path to install CPLEX. In the experiment we choose:
/home/<USER>/CPLEX_Studio221
Note.: Replace <USER> with the proper username.
Follow the instructions provided to install the tool.
At the end of the installation, it is prompted the following command to be executed in order to configure the python API:
sudo python3 /home/<USER>/CPLEX_Studio221/python/setup.py install
The path where CPLEX is installed needs to be inserted on ~/.bashrc file. We can do this by adding the following line a the end of ~/.bashrc:
export PATH=$PATH:/home/<USER>/CPLEX_Studio221/cplex/bin/x86-64_linux
After that, execute:
source .bashrc
To confirm the installation run cplex to enter the CPLEX environment. Press Ctrl+C to exit.
After the installation, run the following command to install docplex:
pip3 install --upgrade docplex
The DOcplex tool is a modeling library used to formulate the optimization model and execute it using CPLEX.
After installing the required software, navigate to the scripts/ directory and run the automate.py script as follows:
python3 install automate.py
This will launch the simulation tool and test each solution presented in the paper.
The results are stored in the scripts/<SOLUTION>/output/ folder.
After the simulation, plots can be generated within the repository’s scripts/plots/ directory by running the following command:
./plot_results.sh
Prior to executing the plot generation script, verify that the results path is properly configured in scripts/plots/prefix.py.
Results for the proposed solutions are available at here and here. The plots can be accessed here.
@inproceedings{luciano-sbrc2025,
author = {Luciano Fraga and Leizer Pinto and Kleber Cardoso},
title = { Efficient Task Orchestration Including Mixed Reality Applications in a Combined Cloud-Edge Infrastructure},
booktitle = {Anais do XLIII Simpósio Brasileiro de Redes de Computadores e Sistemas Distribuídos},
location = {Natal/RN},
year = {2025},
keywords = {},
issn = {2177-9384},
pages = {294--307},
publisher = {SBC},
address = {Porto Alegre, RS, Brasil},
doi = {10.5753/sbrc.2025.5905},
url = {https://sol.sbc.org.br/index.php/sbrc/article/view/35139}}