AI-Driven CPU Resource Management in Cloud Operating Systems

As cloud computing continues to grow, efficient resource management remains a critical aspect of maintaining high-performance and cost-effective cloud infrastructures. CPU resource management in cloud operating systems is a key component that influences the scalability, efficiency, and responsiveness of cloud services. Traditional methods of resource allocation often struggle to adapt to the dynamic nature of cloud environments, where workloads can fluctuate in real time. This paper explores the integration of Artificial Intelligence (AI) in optimizing CPU resource management in cloud systems. By leveraging AI techniques such as machine learning and reinforcement learning, cloud operating systems can automate resource allocation, predict demand, and optimize system performance. The paper discusses the role of AI in enhancing resource efficiency, scalability, and fault tolerance, while also addressing the challenges of implementing AI-driven solutions. The potential of AI to transform the way cloud operating systems manage CPU resources offers exciting possibilities for future developments in cloud technology.

Authors

Publication Details

Journal
Journal of Computer and Communications
Published
2025-01-01
DOI
https://doi.org/10.4236/jcc.2025.136009
Citations
4
Primary Topic
Cloud Computing and Resource Management
Type
article
Field-Weighted Citation Impact
12.98
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article

AI-Driven CPU Resource Management in Cloud Operating Systems

Yihan Wang, Suchuan Xing
4 citations
Journal of Computer and Communications
Cloud Computing and Resource Management
12.98
article

AI-Driven CPU Resource Management in Cloud Operating Systems

Yihan Wang, Suchuan Xing
article en
4 citations

Abstract

As cloud computing continues to grow, efficient resource management remains a critical aspect of maintaining high-performance and cost-effective cloud infrastructures. CPU resource management in cloud operating systems is a key component that influences the scalability, efficiency, and responsiveness of cloud services. Traditional methods of resource allocation often struggle to adapt to the dynamic nature of cloud environments, where workloads can fluctuate in real time. This paper explores the integration of Artificial Intelligence (AI) in optimizing CPU resource management in cloud systems. By leveraging AI techniques such as machine learning and reinforcement learning, cloud operating systems can automate resource allocation, predict demand, and optimize system performance. The paper discusses the role of AI in enhancing resource efficiency, scalability, and fault tolerance, while also addressing the challenges of implementing AI-driven solutions. The potential of AI to transform the way cloud operating systems manage CPU resources offers exciting possibilities for future developments in cloud technology.

Journal of Computer and CommunicationsVol. 13(06)
Decent work and economic growth
Openalex Percentile: Top 2%
Cloud Computing and Resource Management
12.98
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