Machine Learning Project - Task Allocation in Fog and Cloud Computing

This project was carried out as part of the Multi-objective Optimization course, under the supervision of Sonia Yassa.

Project Description

The objective of this project is to optimize task allocation in a Fog Computing and Cloud Computing environment using multi-objective optimization approaches.

Prerequisites

• Python installed on your machine.
• Use an editor like VS Code to run the notebooks.

Notebook Organization

The notebooks should be executed in the following order:

1. 01_data_preparation.ipynb → Generates two CSV files containing tasks and virtual machines (Fog and Cloud).

2. 02_pareto_fronts.ipynb
   → Computes the Pareto fronts using two methods: MOCS and MOFA.

3. 03_pareto_analysis.ipynb → Analyzes the obtained Pareto fronts to compare the performance of the approaches.

4. 04_solution_analysis.ipynb → Studies the distribution of solutions between Fog and Cloud.

Execution

Open and execute the notebooks in VS Code, following the indicated order.