.png){kind=icon}
返回
Optimizing multi-time series forecasting for enhanced cloud resource utilization based on machine learning
.png){kind=icon}
OA
AI
DOI：10.1016/j.knosys.2024.112489.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Due to its flexibility, cloud computing has become essential in modern operational schemes. However, the effective management of cloud resources to ensure cost-effectiveness and maintain high performance presents significant challenges. The pay-as-you-go pricing model, while convenient, can lead to escalated expenses and hinder long-term planning. Consequently, FinOps advocates proactive management strategies, with resource usage prediction emerging as a crucial optimization category. In this research, we introduce the multi time series forecasting system (MSFS), a novel approach for data-driven resource optimization alongside the hybrid ensemble anomaly detection algorithm (HEADA). Our method prioritizes the concept-centric approach, focusing on factors such as prediction uncertainty, interpretability and domain-specific measures. Furthermore, we introduce the similarity-based time-series grouping (STG) method as a core component of MSFS for optimizing multi-time series forecasting, ensuring its scalability with the rapid growth of the cloud environment. The experiments performed demonstrate that our group-specific forecasting model (GSFM) approach enabled MSFS to achieve a significant cost reduction of up to 44%.
Keyword:
Cloud computing
Cloud resource usage optimization
Machine learning
Time series forecasting optimization
Cloud finOps
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
K
IF:
7.6
论文数:
1.3W
被引数:
4.5W
机构
引用论文
Detecting and identifying non-stationary courses in the ripping head power consumption by recurrence plots.png)
Meccanica
MeccanicaIF0
PREAI
分享收藏Stable and efficient resource management using deep neural network on cloud computing云计算环境下基于深度神经网络的稳定高效资源管理NEUROCOMPUTING
NEUROCOMPUTINGIF6.5
PREAI
分享收藏分享收藏Optimization of the Use of Cloud Computing Resources Using Exploratory Data Analysis and Machine Learning使用探索性数据分析和机器学习优化云计算资源的使用
OAAI
OAAI分享收藏
查看更多内容