Learning-Based Virtual Machine Selection in Cloud Server Consolidation
Huixi Li,
Yinhao Xiao,
YongLuo Shen and
Amandeep Kaur
Mathematical Problems in Engineering, 2022, vol. 2022, 1-11
Abstract:
In cloud data center (CDC), reducing energy consumption while maintaining performance has always been a hot issue. In server consolidation, the traditional solution is to divide the problem into multiple small problems such as host overloading detection, virtual machine (VM) selection, and VM placement and solve them step by step. However, the design of host overloading detection strategies and VM selection strategies cannot be directly linked to the ultimate goal of reducing energy consumption and ensuring performance. This paper proposes a learning-based VM selection strategy that selects appropriate VMs for migration without direct host overloading detection, thereby reducing the generation of SLAV, ensuring the performance, and reducing the energy consumption of CDC. Simulations driven by real VM workload traces show that our method outperforms the existing methods in reducing SLAV generation and CDC energy consumption.
Date: 2022
References: Add references at CitEc
Citations:
Downloads: (external link)
http://downloads.hindawi.com/journals/mpe/2022/6853196.pdf (application/pdf)
http://downloads.hindawi.com/journals/mpe/2022/6853196.xml (application/xml)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:6853196
DOI: 10.1155/2022/6853196
Access Statistics for this article
More articles in Mathematical Problems in Engineering from Hindawi
Bibliographic data for series maintained by Mohamed Abdelhakeem ().