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

Autor:	Mokadem, Riad, Arar, Fahem, Zegour, Djamel Eddine
Rok vydání:	2024
Předmět:	Computer Science - Distributed Parallel and Cluster Computing Computer Science - Artificial Intelligence
Zdroj:	Doctoral Conference on computer Science ADCCS'2024, Ecole Sup{\'e}rieure d'Informatique ESI, May 2024, Algier, Algeria
Druh dokumentu:	Working Paper
Popis:	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).
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2410.11862 Zobrazit plný text záznamu View this record from Arxiv