An Adaptive Deployment Algorithm for IaaS Cloud Virtual Machines Based on Q Learning Mechanism
When deploying infrastructure as a service (IaaS) cloud virtual machines using the existing algorithms, the deployment process cannot be simplified, and the algorithm is difficult to be applied. This leads to the problems of high energy consumption, high number of migrations, and high average servic...
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Hindawi Limited
2021
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oai:doaj.org-article:de0ef905e99e4506830f4a7feb4b81da2021-11-08T02:35:42ZAn Adaptive Deployment Algorithm for IaaS Cloud Virtual Machines Based on Q Learning Mechanism1687-726810.1155/2021/2119993https://doaj.org/article/de0ef905e99e4506830f4a7feb4b81da2021-01-01T00:00:00Zhttp://dx.doi.org/10.1155/2021/2119993https://doaj.org/toc/1687-7268When deploying infrastructure as a service (IaaS) cloud virtual machines using the existing algorithms, the deployment process cannot be simplified, and the algorithm is difficult to be applied. This leads to the problems of high energy consumption, high number of migrations, and high average service-level agreement (SLA) violation rate. In order to solve the above problems, an adaptive deployment algorithm for IaaS cloud virtual machines based on Q learning mechanism is proposed in this research. Based on the deployment principle, the deployment characteristics of the IaaS cloud virtual machines are analyzed. The virtual machine scheduling problem is replaced with the Markov process. The multistep Q learning algorithm is used to schedule the virtual machines based on the Q learning mechanism to complete the adaptive deployment of the IaaS cloud virtual machines. Experimental results show that the proposed algorithm has low energy consumption, small number of migrations, and low average SLA violation rate.Shuguang ChenHindawi LimitedarticleTechnology (General)T1-995ENJournal of Sensors, Vol 2021 (2021) |
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Technology (General) T1-995 Shuguang Chen An Adaptive Deployment Algorithm for IaaS Cloud Virtual Machines Based on Q Learning Mechanism |
description |
When deploying infrastructure as a service (IaaS) cloud virtual machines using the existing algorithms, the deployment process cannot be simplified, and the algorithm is difficult to be applied. This leads to the problems of high energy consumption, high number of migrations, and high average service-level agreement (SLA) violation rate. In order to solve the above problems, an adaptive deployment algorithm for IaaS cloud virtual machines based on Q learning mechanism is proposed in this research. Based on the deployment principle, the deployment characteristics of the IaaS cloud virtual machines are analyzed. The virtual machine scheduling problem is replaced with the Markov process. The multistep Q learning algorithm is used to schedule the virtual machines based on the Q learning mechanism to complete the adaptive deployment of the IaaS cloud virtual machines. Experimental results show that the proposed algorithm has low energy consumption, small number of migrations, and low average SLA violation rate. |
format |
article |
author |
Shuguang Chen |
author_facet |
Shuguang Chen |
author_sort |
Shuguang Chen |
title |
An Adaptive Deployment Algorithm for IaaS Cloud Virtual Machines Based on Q Learning Mechanism |
title_short |
An Adaptive Deployment Algorithm for IaaS Cloud Virtual Machines Based on Q Learning Mechanism |
title_full |
An Adaptive Deployment Algorithm for IaaS Cloud Virtual Machines Based on Q Learning Mechanism |
title_fullStr |
An Adaptive Deployment Algorithm for IaaS Cloud Virtual Machines Based on Q Learning Mechanism |
title_full_unstemmed |
An Adaptive Deployment Algorithm for IaaS Cloud Virtual Machines Based on Q Learning Mechanism |
title_sort |
adaptive deployment algorithm for iaas cloud virtual machines based on q learning mechanism |
publisher |
Hindawi Limited |
publishDate |
2021 |
url |
https://doaj.org/article/de0ef905e99e4506830f4a7feb4b81da |
work_keys_str_mv |
AT shuguangchen anadaptivedeploymentalgorithmforiaascloudvirtualmachinesbasedonqlearningmechanism AT shuguangchen adaptivedeploymentalgorithmforiaascloudvirtualmachinesbasedonqlearningmechanism |
_version_ |
1718443237358698496 |