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Towards a resource migration method in cloud computing based on node failure rule.

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Title: Towards a resource migration method in cloud computing based on node failure rule.
Authors: Zhigao Zheng1, Tao Huang2, Hao Zhang2 haozhang@whu.edu.cn, Shenli Sun3, Jinming Wen4, Ping Wang3
Source: Journal of Intelligent & Fuzzy Systems. 2016, Vol. 31 Issue 4, p2611-2618. 8p.
Subjects: Cloud computing, Failure Analysis System (Computer system), Virtual machine systems, Statistical reliability, Threshold concepts (Learning)
Abstract: The virtualization design management and adaptive resource migration techniques are typically used for energy saving and system reliability improvement in the cloud computing system. The paper presents a resource migration technique based on node performance and failure rule (NPFR-RMT). It uses Broker to access node performance to determine abnormal nodes and failure nodes. All nodes in the idle queue are conducted failure rule detection with failure model. The fast and slow nodes are determined by node performance threshold analysis. The NPFR-RMT adds slow nodes and failure nodes into idle queue. The virtual machine (VM) migration method is also adapted to migrate tasks to normal nodes in idle queue for re-execution. Comparison experiment results show that the NPFR-RMT method presented in the paper can achieve expected aim that reducing energy consumption of data centers while ensuring service performance. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Intelligent & Fuzzy Systems is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Towards a resource migration method in cloud computing based on node failure rule.
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  Data: <searchLink fieldCode="AR" term="%22Zhigao+Zheng%22">Zhigao Zheng</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Tao+Huang%22">Tao Huang</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AR" term="%22Hao+Zhang%22">Hao Zhang</searchLink><relatesTo>2</relatesTo><i> haozhang@whu.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Shenli+Sun%22">Shenli Sun</searchLink><relatesTo>3</relatesTo><br /><searchLink fieldCode="AR" term="%22Jinming+Wen%22">Jinming Wen</searchLink><relatesTo>4</relatesTo><br /><searchLink fieldCode="AR" term="%22Ping+Wang%22">Ping Wang</searchLink><relatesTo>3</relatesTo>
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  Data: <searchLink fieldCode="DE" term="%22Cloud+computing%22">Cloud computing</searchLink><br /><searchLink fieldCode="DE" term="%22Failure+Analysis+System+%28Computer+system%29%22">Failure Analysis System (Computer system)</searchLink><br /><searchLink fieldCode="DE" term="%22Virtual+machine+systems%22">Virtual machine systems</searchLink><br /><searchLink fieldCode="DE" term="%22Statistical+reliability%22">Statistical reliability</searchLink><br /><searchLink fieldCode="DE" term="%22Threshold+concepts+%28Learning%29%22">Threshold concepts (Learning)</searchLink>
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  Data: The virtualization design management and adaptive resource migration techniques are typically used for energy saving and system reliability improvement in the cloud computing system. The paper presents a resource migration technique based on node performance and failure rule (NPFR-RMT). It uses Broker to access node performance to determine abnormal nodes and failure nodes. All nodes in the idle queue are conducted failure rule detection with failure model. The fast and slow nodes are determined by node performance threshold analysis. The NPFR-RMT adds slow nodes and failure nodes into idle queue. The virtual machine (VM) migration method is also adapted to migrate tasks to normal nodes in idle queue for re-execution. Comparison experiment results show that the NPFR-RMT method presented in the paper can achieve expected aim that reducing energy consumption of data centers while ensuring service performance. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Journal of Intelligent & Fuzzy Systems is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.3233/JIFS-169101
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        Text: English
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        PageCount: 8
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      – SubjectFull: Virtual machine systems
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      – SubjectFull: Threshold concepts (Learning)
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            NameFull: Jinming Wen
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            NameFull: Ping Wang
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              Text: 2016
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