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The Green Scheduling Architecture for the Virtual Resource Supply

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Abstract

The data center is a large cluster system. The IT clusters provide users with various services and resources, which make decentralized energy consumption over the past come together, resulting in great energy consumption of the data center. Rational resource allocation of virtual machine is an efficient way to reduce energy consumption. This paper proposed a green scheduling framework for the virtual resource supply GS_VRS to reduce the energy consumption of center as a goal. Through the multiobjective optimization of scheduling and migration of virtual machines, this framework can efficiently reduce the energy consumption of data center. Compared with other representative strategy, the experiment result showed that strategy proposed in this paper not only reduced energy consumption, but also considered the network flow, migration costs, performance interference and many other aspects, the GS_VRS algorithm proposed in this paper can efficiently reduce the energy consumption of data center which averaged 49.78% less on average than the most energy-intensive random algorithm.

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Funding

This work was supported in part by the science and technology project of “14th Five-Year” planning of the Education Department of Jilin Province (JJKH20220922KJ); the reform of vocational and adult education of the Education Department of Jilin Province (2020ZCY348); and research topic of higher education teaching reform in Jilin Province (20213F28H04001O).

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Authors and Affiliations

  1. Jilin Provincial Institute of Education, 130022, Changchun, Jilin, China

    Xin Sui

  2. Changchun University of Science and Technology, College of Computer Science and Technology, 130022, Changchun, Jilin, China

    Leilei Zhu, Xiaolong Song, Guoyu Sheng & Dan Liu

Authors
  1. Xin Sui
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  2. Leilei Zhu
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  3. Xiaolong Song
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  4. Guoyu Sheng
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  5. Dan Liu
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Corresponding author

Correspondence to Dan Liu.

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Xin Sui, Zhu, L., Song, X. et al. The Green Scheduling Architecture for the Virtual Resource Supply. Aut. Control Comp. Sci. 57, 14–26 (2023). https://doi.org/10.3103/S0146411623010108

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