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2020 – today
- 2024
[j10]Yisel Gari
, Elina Pacini, Luciano Robino, Cristian Mateos, David A. Monge:
Online RL-based cloud autoscaling for scientific workflows: Evaluation of Q-Learning and SARSA. Future Gener. Comput. Syst. 157: 573-586 (2024)- 2022
- [j9]Yisel Gari, David A. Monge, Cristian Mateos:
A Q-learning approach for the autoscaling of scientific workflows in the Cloud. Future Gener. Comput. Syst. 127: 168-180 (2022) - 2021
- [j8]Yisel Gari, David A. Monge, Elina Pacini, Cristian Mateos, Carlos García Garino:
Reinforcement learning-based application Autoscaling in the Cloud: A survey. Eng. Appl. Artif. Intell. 102: 104288 (2021) - [c8]Virginia Yannibelli, Elina Pacini, David A. Monge, Cristian Mateos, Guillermo Rodríguez:
Endowing the MIA Cloud Autoscaler with Adaptive Evolutionary and Particle Swarm Multi-Objective Optimization Algorithms. MICAI (1) 2021: 383-400 - 2020
- [j7]Yisel Gari, David A. Monge, Cristian Mateos, Carlos García Garino:
Learning budget assignment policies for autoscaling scientific workflows in the cloud. Clust. Comput. 23(1): 87-105 (2020) - [j6]David A. Monge, Elina Pacini, Cristian Mateos, Enrique Alba, Carlos García Garino:
CMI: An online multi-objective genetic autoscaler for scientific and engineering workflows in cloud infrastructures with unreliable virtual machines. J. Netw. Comput. Appl. 149 (2020) - [j5]Virginia Yannibelli, Elina Pacini, David A. Monge, Cristian Mateos, Guillermo Rodríguez:
A Comparative Analysis of NSGA-II and NSGA-III for Autoscaling Parameter Sweep Experiments in the Cloud. Sci. Program. 2020: 4653204:1-4653204:17 (2020) - [c7]Virginia Yannibelli, Elina Pacini, David A. Monge, Cristian Mateos, Guillermo Rodríguez:
An NSGA-III-Based Multi-objective Intelligent Autoscaler for Executing Engineering Applications in Cloud Infrastructures. MICAI (1) 2020: 249-263 - [i2]Yisel Gari, David A. Monge, Elina Pacini, Cristian Mateos, Carlos García Garino:
Reinforcement Learning-based Autoscaling of Workflows in the Cloud: A Survey. CoRR abs/2001.09957 (2020)
2010 – 2019
- 2018
- [j4]David A. Monge, Elina Pacini, Cristian Mateos, Carlos García Garino:
Meta-heuristic based autoscaling of cloud-based parameter sweep experiments with unreliable virtual machines instances. Comput. Electr. Eng. 69: 364-377 (2018) - [i1]David A. Monge, Elina Pacini, Cristian Mateos, Enrique Alba, Carlos García Garino:
CMI: An Online Multi-objective Genetic Autoscaler for Scientific and Engineering Workflows in Cloud Infrastructures with Unreliable Virtual Machines. CoRR abs/1811.00989 (2018) - 2017
- [j3]David A. Monge, Yisel Gari, Cristian Mateos, Carlos García Garino:
Autoscaling scientific workflows on the cloud by combining on-demand and spot instances. Comput. Syst. Sci. Eng. 32(4) (2017) - [c6]Josef Spillner, Cristian Mateos, David A. Monge:
FaaSter, Better, Cheaper: The Prospect of Serverless Scientific Computing and HPC. CARLA 2017: 154-168 - [c5]Yisel Gari, David A. Monge, Cristian Mateos, Carlos García Garino:
Markov Decision Process to Dynamically Adapt Spots Instances Ratio on the Autoscaling of Scientific Workflows in the Cloud. CARLA 2017: 353-369 - [c4]Matías Hirsch, Cristian Mateos, Juan Manuel Rodriguez, Alejandro Zunino, Yisel Gari, David A. Monge:
A performance comparison of data-aware heuristics for scheduling jobs in mobile grids. CLEI 2017: 1-8 - 2015
- [j2]David A. Monge, Matej Holec, Filip Zelezný, Carlos García Garino:
Ensemble learning of runtime prediction models for gene-expression analysis workflows. Clust. Comput. 18(4): 1317-1329 (2015) - 2014
- [j1]David A. Monge, Carlos García Garino:
LOGOS: Enabling Local Resource Managers for the Efficient Support of Data-Intensive Workflows within Grid Sites. Comput. Informatics 33(1): 109-130 (2014) - [c3]David A. Monge, Carlos García Garino:
Adaptive Spot-Instances Aware Autoscaling for Scientific Workflows on the Cloud. CARLA 2014: 13-27 - [c2]David A. Monge, Matej Holec, Filip Zelezný, Carlos García Garino:
Ensemble Learning of Run-Time Prediction Models for Data-Intensive Scientific Workflows. CARLA 2014: 83-97 - 2011
- [c1]Jiri Belohradsky, David A. Monge, Filip Zelezný, Matej Holec, Carlos García Garino:
Template-based semi-automatic workflow construction for gene expression data analysis. CBMS 2011: 1-6
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