Authors: Yulu Gong, Jiaxin Huang, Bo Liu, Jingyu Xu, Binbin Wu, Yifan Zhang

Published on: March 20, 2024

Impact Score: 7.6

Arxiv code: Arxiv:2403.13619

Summary

• What is new: Introduces machine learning-based optimization for virtual machine migration and dynamic resource allocation in cloud computing.
• Why this is important: The need for efficient data access, storage, and the prevention of time delays in utilizing cloud computing services.
• What the research proposes: Applying machine learning algorithms to optimize virtual machine migration and dynamic resource allocation in cloud environments.
• Results: Contributions to expanding cloud services and addressing the limitations of static rules or manual settings in cloud computing.

Technical Details

Technological frameworks used: Machine Learning-based optimization

Models used: nan

Data used: nan

Potential Impact

Cloud service providers, data storage companies, and businesses reliant on efficient cloud computing services.

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