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In this work, we analyze and evaluate two important algorithms in this area: Q-Learning [3] and SARSA [4] (State-Action-Reward-State-Action) that have been�...
Jul 18, 2024 � Results show that SARSA outperforms Q-Learning in almost all cases. For two workflows SARSA obtains significant gains of up to 40.8% in the�...
Results show that SARSA outperforms Q-Learning in almost all cases. For two workflows SARSA obtains significant gains of up to 40.8% in the first 100 and 300�...
The proposed approach is divided into two processes: task prioritization and resource selection. In this article, initially, the tasks are prioritized by using�...
Online RL-based cloud autoscaling for scientific workflows: Evaluation of Q-Learning and SARSA. https://doi.org/10.1016/j.future.2024.04.014 �.
This project contains the runnable code for the experiments of the work "Evaluation of Q-Learning and SARSA in the context of Cloud Autoscaling for Scientific�...
Online RL-based cloud autoscaling for scientific workflows: Evaluation of Q-Learning and SARSA. Y Gar�, E Pacini, L Robino, C Mateos, DA Monge. Future�...
Autoscaling exploits the Cloud elasticity to optimize the execution of applica- tions according to given optimization criteria, which demands to decide when and�...
Autoscaling strategies aim to exploit the elasticity, resource heterogeneity and varied prices options of a Cloud infrastructure to improve efficiency in�...
Article "Online RL-based cloud autoscaling for scientific workflows: Evaluation of Q-Learning and SARSA" Detailed information of the J-GLOBAL is an�...