mlsanityData to 7 Oct 2026

Machine learning for cloud resources management -- An overview

arXiv 2101.11984 ↗First posted 28 Jan 2021cs.LG cs.NIcited by 2

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Abstract (arXiv)

Nowadays, an important topic that is considered a lot is how to integrate Machine Learning(ML) to cloud resources management. In this study, our goal is to explore the most important cloud resources management issues that have been combined with ML and which present many promising results. To accomplish this, we used chronological charts based on some keywords that we considered important and tried to answer the question: is ML suitable for resources management problems in the cloud? Furthermore, a short discussion takes place on the data that are available and the open challenges on it. A big collection of researches is used to make sensible comparisons between the ML techniques that are used in the different kinds of cloud resources management fields and we propose the most suitable ML model for each field. 1

Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 1 of its 28 references that are in the map. First posted on arXiv 28 Jan 2021.

Builds on

1 of 28 references.

References · 1

  1. 2017A Hierarchical Framework of Cloud Resource Allocation and Power Management Using Deep Reinforcement Learningcited by 16

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Citing papers per year: 2021: 1; 2022: 1.

2 papers.