Virtual machine scheduling model based on Shapley value modified genetic algorithm in cloud computing
Cloud computing system has the characteristics of large-scale servers and a wide range of users.However, it also consumes a huge number of energy, resulting in high operating costs of cloud providers and high carbon emissions issue.Cloud computing is highly virtualized.How to allocate and manage the...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | zho |
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Beijing Xintong Media Co., Ltd
2022-12-01
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| Series: | Dianxin kexue |
| Subjects: | |
| Online Access: | http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2022281/ |
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| _version_ | 1841530797309296640 |
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| author | Kun MA Lingyu XU Xiaoping SHEN Zhicheng GONG Jianping LAN Shuangxi CHEN Jun QIAN |
| author_facet | Kun MA Lingyu XU Xiaoping SHEN Zhicheng GONG Jianping LAN Shuangxi CHEN Jun QIAN |
| author_sort | Kun MA |
| collection | DOAJ |
| description | Cloud computing system has the characteristics of large-scale servers and a wide range of users.However, it also consumes a huge number of energy, resulting in high operating costs of cloud providers and high carbon emissions issue.Cloud computing is highly virtualized.How to allocate and manage the virtual resources to ensure efficient physical resource utilization and energy consumption control is a multi-parameter game problem, and it is also a research hotspot in this field.A virtual machine scheduling model and the corresponding SV-GA were proposed, which could calculate the contribution value of the physical machine participating in the work through the Shapley value, and modify the probability parameter of the mutation step in the genetic algorithm through the contribution value, so as to complete the task of virtual machine scheduling.The experimental results show that during the comparison with Max-Min, LrMmt and DE, the SV-GA shows its excellent performance in the multi-parameter game including migration time, times, SLA violation rate and energy consumption in the virtual machine scheduling process. |
| format | Article |
| id | doaj-art-f7fb65a4f58745fbabf426b5a49844d5 |
| institution | Kabale University |
| issn | 1000-0801 |
| language | zho |
| publishDate | 2022-12-01 |
| publisher | Beijing Xintong Media Co., Ltd |
| record_format | Article |
| series | Dianxin kexue |
| spelling | doaj-art-f7fb65a4f58745fbabf426b5a49844d52025-01-15T02:59:44ZzhoBeijing Xintong Media Co., LtdDianxin kexue1000-08012022-12-013811059574178Virtual machine scheduling model based on Shapley value modified genetic algorithm in cloud computingKun MALingyu XUXiaoping SHENZhicheng GONGJianping LANShuangxi CHENJun QIANCloud computing system has the characteristics of large-scale servers and a wide range of users.However, it also consumes a huge number of energy, resulting in high operating costs of cloud providers and high carbon emissions issue.Cloud computing is highly virtualized.How to allocate and manage the virtual resources to ensure efficient physical resource utilization and energy consumption control is a multi-parameter game problem, and it is also a research hotspot in this field.A virtual machine scheduling model and the corresponding SV-GA were proposed, which could calculate the contribution value of the physical machine participating in the work through the Shapley value, and modify the probability parameter of the mutation step in the genetic algorithm through the contribution value, so as to complete the task of virtual machine scheduling.The experimental results show that during the comparison with Max-Min, LrMmt and DE, the SV-GA shows its excellent performance in the multi-parameter game including migration time, times, SLA violation rate and energy consumption in the virtual machine scheduling process.http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2022281/cloud computingmulti-parameter gamevirtual machine schedulingShapley valuegenetic algorithm |
| spellingShingle | Kun MA Lingyu XU Xiaoping SHEN Zhicheng GONG Jianping LAN Shuangxi CHEN Jun QIAN Virtual machine scheduling model based on Shapley value modified genetic algorithm in cloud computing Dianxin kexue cloud computing multi-parameter game virtual machine scheduling Shapley value genetic algorithm |
| title | Virtual machine scheduling model based on Shapley value modified genetic algorithm in cloud computing |
| title_full | Virtual machine scheduling model based on Shapley value modified genetic algorithm in cloud computing |
| title_fullStr | Virtual machine scheduling model based on Shapley value modified genetic algorithm in cloud computing |
| title_full_unstemmed | Virtual machine scheduling model based on Shapley value modified genetic algorithm in cloud computing |
| title_short | Virtual machine scheduling model based on Shapley value modified genetic algorithm in cloud computing |
| title_sort | virtual machine scheduling model based on shapley value modified genetic algorithm in cloud computing |
| topic | cloud computing multi-parameter game virtual machine scheduling Shapley value genetic algorithm |
| url | http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2022281/ |
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