Machine learning for cloud resources management -- An overview
It addresses the problem of optimizing cloud resource management for cloud providers and users, but it is incremental as it synthesizes existing research rather than introducing new methods.
This paper provides an overview of how machine learning is integrated into cloud resource management, exploring key issues and proposing suitable ML models for different fields based on a collection of research.
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