Given its intuitive nature, many Cloud providers opt for threshold-based data replication to enable automatic resource scaling. However, setting thresholds effectively needs human intervention to calibrate thresholds for each metric and requires a deep knowledge of current workload trends, which can be challenging to achieve. Reinforcement learning is used in many areas related to the Cloud Computing, and it is a promising field to get automatic data replication strategies. In this work, we survey data replication strategies and data scaling based on reinforcement learning (RL).
@article{arxiv.2410.11862,
title = {Towards using Reinforcement Learning for Scaling and Data Replication in Cloud Systems},
author = {Riad Mokadem and Fahem Arar and Djamel Eddine Zegour},
journal= {arXiv preprint arXiv:2410.11862},
year = {2024}
}