A Hybird Virtual Machine Placement Aglrithm for Virtualized Desktop Infrastructure

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Abstract:

As we all kown, The virtual machine placement is one kind of bin-packing problem. By optimizing placement of virtual machine. We can improve VM performance, enhance resource utilization, reduce energy comsumption. After analysis the existing virtual machine placement aglrithm. We propose a hybird virtual machine placement aglrithm (HTA) which based on network latency threshold for the requirement of low network latence and low VM migraiton ratio in Virtualized Desktop Infrastructure. It elect qualified node set based on network latency threshold and palce the virtual machines with load-balance policy, taking into account the preformance of the network and vitual machines. According to analysis and comparison. The simulation result show that the algorithm can effectively lessen the network latency and reduce the VM migration ratio.

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Periodical:

Advanced Materials Research (Volumes 760-762)

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1906-1910

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September 2013

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© 2013 Trans Tech Publications Ltd. All Rights Reserved

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[1] ANH Vu Do, Chen Junliang, Wang Cheng, et al. Profiling Applications for Virtual Machine Placement in Clouds: [C]/Clound Computing(CLOUD). Washington, DC: 2011: 660-667.

Google Scholar

[2] JING Tai Piao, Jun Yan. A Network-aware Virtual Machine Placement and Migration Approach in Cloud Computing: [C]/Grid and Cooperative Computing(GCC). Nanjing: 2010: 87-92.

DOI: 10.1109/gcc.2010.29

Google Scholar

[3] Bobroff N, Kochut A, Beaty K. Dynamic Placement of Virtual Machines for Managing SLA Violations: [C]/Integrated Network Management. Munich: 2007: 119-128.

DOI: 10.1109/inm.2007.374776

Google Scholar

[4] CAO Le, THANH Man, Makoto Kayashima. Virtual machine placement algorithm for virtualized desktop infrastructure: [C]/Cloud Computing and Intelligence Systems (CCIS). Beijing: 2011: 333-337.

DOI: 10.1109/ccis.2011.6045085

Google Scholar

[5] Van HN, Tran FD, Menaud JM. SLA-Aware Virtual Resource Management for Cloud Infrastructures: [C]/Computer and Information Technology. Xiamen: 2009: 357-362.

DOI: 10.1109/cit.2009.109

Google Scholar

[6] Charisiri S, Lee BS, Niyato D. Optimal virtual machine placement across multiple cloud providers: [C]/Services Computing Conference. Singapore: 2009: 103-110.

DOI: 10.1109/apscc.2009.5394134

Google Scholar

[7] MillS KJ Filliben, Dabrowski C. Comparing VM-Placement Algorithms for On-Demand Clounds: [C]/Cloud Computing Technology and Science(CloudCom). Athens: 2011: 91-98.

DOI: 10.1109/cloudcom.2011.22

Google Scholar

[8] Harper RE, Lorrie Tomek, Ofer Biran, et al. A virtual resource placement service: [C]/Dependable Systems and Networks Workshops(DSN-W). HongKong: 2011: 158-163.

DOI: 10.1109/dsnw.2011.5958803

Google Scholar

[9] Mark CCT, Niyato D, Tham Chen-Khong. Evolutionary Optimal Placement and Demand Forecaster for Cloud Computing: [C]/Advanced Information Networking and Application(AINA). Biopolis: 2011: 348-355.

DOI: 10.1109/aina.2011.50

Google Scholar

[10] Le Kien, Zhang Jingru, Meng Jiangdong. Reducing electricity cost through virtual machine placement in high performance computing clouds: [C]/High Performance Computing, Networking, Storage and Analysis(SC). Seatle, WA: 2011: 1-12.

DOI: 10.1145/2063384.2063413

Google Scholar