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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Autor principal: Shuguang Chen
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Publicado: Hindawi Limited 2021
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Acceso en línea:https://doaj.org/article/de0ef905e99e4506830f4a7feb4b81da
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spelling 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)
institution DOAJ
collection DOAJ
language EN
topic Technology (General)
T1-995
spellingShingle 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
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