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arXiv · 2410.11862

Towards using Reinforcement Learning for Scaling and Data Replication in Cloud Systems

Riad Mokadem·Fahem Arar·Djamel Eddine Zegour
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Abstract

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).

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Riad Mokadem, Fahem Arar, Djamel Eddine Zegour. 2024-10-07. Towards using Reinforcement Learning for Scaling and Data Replication in Cloud Systems. https://arxiv.org/abs/2410.11862

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