Global detection of live virtual machine migration based on cellular neural networks.
In order to meet the demands of operation monitoring of large scale, autoscaling, and heterogeneous virtual resources in the existing cloud computing, a new method of live virtual machine (VM) migration detection algorithm based on the cellular neural networks (CNNs), is presented. Through analyzing...
| Publicado en: | Scientific World Journal pp. 829614 - 829615 |
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| Autores principales: | , , , , , |
| Formato: | research Journal Article |
| Publicado: |
Wiley-Blackwell
2014
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=103830670&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 103830670 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 1537744X 1BX5 jtl: Scientific World Journal issn: 1537744X maglogo: N pubinfo: dt: 2014 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 103830670 103830670 NLM24959631 2012628966 10.1155/2014/829614 NLM24959631 PMC4052617 103830670 ppf: 829614 ppct: 1 formats: tig: atl: Global detection of live virtual machine migration based on cellular neural networks. aug: au: Xie, Kang Yang, Yixian Zhang, Ling Jing, Maohua Xin, Yang Li, Zhongxian affil: College of Information Science and Engineering, Shandong University, Jinan 250100, China. sug: subj: Artificial Intelligence Neural Networks (Computer) Algorithms ab: In order to meet the demands of operation monitoring of large scale, autoscaling, and heterogeneous virtual resources in the existing cloud computing, a new method of live virtual machine (VM) migration detection algorithm based on the cellular neural networks (CNNs), is presented. Through analyzing the detection process, the parameter relationship of CNN is mapped as an optimization problem, in which improved particle swarm optimization algorithm based on bubble sort is used to solve the problem. Experimental results demonstrate that the proposed method can display the VM migration processing intuitively. Compared with the best fit heuristic algorithm, this approach reduces the processing time, and emerging evidence has indicated that this new approach is affordable to parallelism and analog very large scale integration (VLSI) implementation allowing the VM migration detection to be performed better. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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