All related repositories are also available at: https://github.com/topics/pid2021-128071ob-i00
software & tools | open science & research experiments | datasets
Software & tools
GeneticHybridizationPlacement is a Python-based ecosystem for the optimization of resource placement in fog computing environments using Genetic Algorithms (GAs). The framework supports both single-algorithm and hybrid-algorithm evolutionary strategies, enabling comprehensive experimentation and benchmarking.
Public repository
Open science & research experiments
Data and source code repositories for the reproducibility and the replicability of the results of the project.
All those repositories are listed at https://github.com/topics/pid2021-128071ob-i00
Paper: Optimizing fog colony layout and service placement through genetic algorithms and hierarchical clustering (https://doi.org/10.1016/j.eswa.2024.124372)
Source code & data: https://github.com/acsicuib/GA-hierarchical-clustering
Paper: Distributed genetic algorithm for application placement in the compute continuum leveraging infrastructure nodes for optimization (https://doi.org/10.1016/j.future.2024.05.044)
Source code & data: https://github.com/acsicuib/GAmqtt
Datasets