LVMM: A lightweight virtual machine memory management architecture for virtual computing environment

Weizhe Zhang; Cheng Tao; Hui He; Albert M.K. Cheng

doi:10.1109/URKE.2011.6007806

LVMM: A lightweight virtual machine memory management architecture for virtual computing environment

Weizhe Zhang^*
, Cheng Tao
, Hui He
, Albert M.K. Cheng

^*Corresponding author for this work

School of Computer Science and Technology, Harbin Institute of Technology
University of Houston

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

3 Scopus citations

Abstract

Virtualization technology recently becomes a hot research topic again in both industry and academics. Some physical hardware such as processors and I/O devices are shared among virtual machines using time slicing, but the memory resource management is relatively complicated. A lightweight memory management architecture for multiple virtual machines is proposed, and it includes a mixture of self-adjustment and global-adjustment policies, both of which collaborate with each other to improve the memory efficiency. Experimental results show that our memory management method is effective, and significantly increase the performance of overall system about 20-30%.

Original language	English
Title of host publication	Proceedings of the International Conference on Uncertainty Reasoning and Knowledge Engineering, URKE 2011
Pages	235-238
Number of pages	4
DOIs	https://doi.org/10.1109/URKE.2011.6007806
State	Published - 2011
Externally published	Yes
Event	2011 International Conference on Uncertainty Reasoning and Knowledge Engineering, URKE 2011 - Bali, Indonesia Duration: 4 Aug 2011 → 7 Aug 2011

Publication series

Name	Proceedings of the International Conference on Uncertainty Reasoning and Knowledge Engineering, URKE 2011
Volume	1

Conference

Conference	2011 International Conference on Uncertainty Reasoning and Knowledge Engineering, URKE 2011
Country/Territory	Indonesia
City	Bali
Period	4/08/11 → 7/08/11

Keywords

global-adjustment
memory management
self-adjustment
virtual machine

Access to Document

10.1109/URKE.2011.6007806

Cite this

Zhang, W., Tao, C., He, H., & Cheng, A. M. K. (2011). LVMM: A lightweight virtual machine memory management architecture for virtual computing environment. In Proceedings of the International Conference on Uncertainty Reasoning and Knowledge Engineering, URKE 2011 (pp. 235-238). Article 6007806 (Proceedings of the International Conference on Uncertainty Reasoning and Knowledge Engineering, URKE 2011; Vol. 1). https://doi.org/10.1109/URKE.2011.6007806

Zhang, Weizhe ; Tao, Cheng ; He, Hui et al. / LVMM : A lightweight virtual machine memory management architecture for virtual computing environment. Proceedings of the International Conference on Uncertainty Reasoning and Knowledge Engineering, URKE 2011. 2011. pp. 235-238 (Proceedings of the International Conference on Uncertainty Reasoning and Knowledge Engineering, URKE 2011).

@inproceedings{0373ff0bb8174d169868a6d56b59d806,

title = "LVMM: A lightweight virtual machine memory management architecture for virtual computing environment",

abstract = "Virtualization technology recently becomes a hot research topic again in both industry and academics. Some physical hardware such as processors and I/O devices are shared among virtual machines using time slicing, but the memory resource management is relatively complicated. A lightweight memory management architecture for multiple virtual machines is proposed, and it includes a mixture of self-adjustment and global-adjustment policies, both of which collaborate with each other to improve the memory efficiency. Experimental results show that our memory management method is effective, and significantly increase the performance of overall system about 20-30\%.",

keywords = "global-adjustment, memory management, self-adjustment, virtual machine",

author = "Weizhe Zhang and Cheng Tao and Hui He and Cheng, \{Albert M.K.\}",

year = "2011",

doi = "10.1109/URKE.2011.6007806",

language = "英语",

isbn = "9781424499830",

series = "Proceedings of the International Conference on Uncertainty Reasoning and Knowledge Engineering, URKE 2011",

pages = "235--238",

booktitle = "Proceedings of the International Conference on Uncertainty Reasoning and Knowledge Engineering, URKE 2011",

note = "2011 International Conference on Uncertainty Reasoning and Knowledge Engineering, URKE 2011 ; Conference date: 04-08-2011 Through 07-08-2011",

}

Zhang, W, Tao, C, He, H & Cheng, AMK 2011, LVMM: A lightweight virtual machine memory management architecture for virtual computing environment. in Proceedings of the International Conference on Uncertainty Reasoning and Knowledge Engineering, URKE 2011., 6007806, Proceedings of the International Conference on Uncertainty Reasoning and Knowledge Engineering, URKE 2011, vol. 1, pp. 235-238, 2011 International Conference on Uncertainty Reasoning and Knowledge Engineering, URKE 2011, Bali, Indonesia, 4/08/11. https://doi.org/10.1109/URKE.2011.6007806

LVMM: A lightweight virtual machine memory management architecture for virtual computing environment. / Zhang, Weizhe; Tao, Cheng; He, Hui et al.
Proceedings of the International Conference on Uncertainty Reasoning and Knowledge Engineering, URKE 2011. 2011. p. 235-238 6007806 (Proceedings of the International Conference on Uncertainty Reasoning and Knowledge Engineering, URKE 2011; Vol. 1).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

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AU - Zhang, Weizhe

AU - Tao, Cheng

AU - He, Hui

AU - Cheng, Albert M.K.

PY - 2011

Y1 - 2011

N2 - Virtualization technology recently becomes a hot research topic again in both industry and academics. Some physical hardware such as processors and I/O devices are shared among virtual machines using time slicing, but the memory resource management is relatively complicated. A lightweight memory management architecture for multiple virtual machines is proposed, and it includes a mixture of self-adjustment and global-adjustment policies, both of which collaborate with each other to improve the memory efficiency. Experimental results show that our memory management method is effective, and significantly increase the performance of overall system about 20-30%.

AB - Virtualization technology recently becomes a hot research topic again in both industry and academics. Some physical hardware such as processors and I/O devices are shared among virtual machines using time slicing, but the memory resource management is relatively complicated. A lightweight memory management architecture for multiple virtual machines is proposed, and it includes a mixture of self-adjustment and global-adjustment policies, both of which collaborate with each other to improve the memory efficiency. Experimental results show that our memory management method is effective, and significantly increase the performance of overall system about 20-30%.

KW - global-adjustment

KW - memory management

KW - self-adjustment

KW - virtual machine

UR - https://www.scopus.com/pages/publications/80053097625

U2 - 10.1109/URKE.2011.6007806

DO - 10.1109/URKE.2011.6007806

M3 - 会议稿件

AN - SCOPUS:80053097625

SN - 9781424499830

T3 - Proceedings of the International Conference on Uncertainty Reasoning and Knowledge Engineering, URKE 2011

SP - 235

EP - 238

BT - Proceedings of the International Conference on Uncertainty Reasoning and Knowledge Engineering, URKE 2011

Y2 - 4 August 2011 through 7 August 2011

ER -

Zhang W, Tao C, He H, Cheng AMK. LVMM: A lightweight virtual machine memory management architecture for virtual computing environment. In Proceedings of the International Conference on Uncertainty Reasoning and Knowledge Engineering, URKE 2011. 2011. p. 235-238. 6007806. (Proceedings of the International Conference on Uncertainty Reasoning and Knowledge Engineering, URKE 2011). doi: 10.1109/URKE.2011.6007806

LVMM: A lightweight virtual machine memory management architecture for virtual computing environment

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