篇名 |
Mitigating Cloud Computing Virtualization Performance Problems with an Upgraded Logical Convergence Strategy
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並列篇名 | Mitigating Cloud Computing Virtualization Performance Problems with an Upgraded Logical Convergence Strategy |
作者 | Ming Zhao、Zhen Wang、Yalong Li、Xiumei Qin |
英文摘要 | In the domain of cloud computing and network resource virtualization, existing fusion techniques for containers and virtual machines suffer from high energy consumption, inflexible scheduling requirements, and suboptimal resource utilization. This study critically examined the current methods, accounted for the contemporary requirements, and developed a novel strategy aimed at maximizing resource utilization while minimizing energy consumption. Comprehensive experiments illustrate the superiority of our approach over state-of-the-art fusion strategies such as Kubernetes+Kubevirt and OpenStack+Kubernetes, demonstrating significant reductions in energy consumption, improved resource utilization, and enhanced system performance.
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起訖頁 | 133-143 |
關鍵詞 | cloud computing、container、logical convergence、deep learning、network resource virtualization、virtual machine |
刊名 | 電腦學刊 |
期數 | 202312 (34:6期) |
DOI |
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QR Code | |
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| Design of An Intelligent Monitoring and Control System for Photovoltaic Microgrids |