Virtual resource monitoring in cloud computing

Cloud computing is a new computing model. The resource monitoring tools are immature compared to traditional distributed computing and grid computing. In order to better monitor the virtual resource in cloud computing, a periodically and event-driven push （PEP） monitoring model is proposed. Taking a...

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Published inJournal of Shanghai University Vol. 15; no. 5; pp. 381 - 385
Main Author 韩芳芳 彭俊杰 张武 李青 李建敦 江钦龙 袁勤
Format Journal Article
LanguageEnglish
Published Heidelberg Shanghai University Press 01.10.2011
School of Computer Engineering and Science, Shanghai University, Shanghai 200072, P.R.China%School of Computer Engineering and Science, Shanghai University, Shanghai 200072, P.R.China
Key Laboratory of Computer System and Architecture, Institute of Computing Technology, Chinese Academy of Science,Beijing 100190, P.R.China
Subjects
Central processing units
Classical Mechanics
Cloud computing
Computation
Computational grids
Computer programs
Engineering
Environment
Information Technology
Intervals
Life Sciences
Materials Science
Mathematical and Computational Engineering
Mechatronics
Monitoring
Monitors
事件驱动机制
分布式计算
监控工具
监测模型
网格计算
虚拟资源
计算模型
资源监控
virtualization
cloud computing
virtual resource monitoring
Online AccessGet full text
ISSN1007-6417
1863-236X
DOI10.1007/s11741-011-0755-1

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Abstract Cloud computing is a new computing model. The resource monitoring tools are immature compared to traditional distributed computing and grid computing. In order to better monitor the virtual resource in cloud computing, a periodically and event-driven push （PEP） monitoring model is proposed. Taking advantage of the push and event-driven mechanism, the model can provide comparatively adequate information about usage and status of the resources. It can simplify the communication between Master and Work Nodes without missing the important issues happened during the push interval. Besides, we develop ＂mon＂ to make up for the deficiency of Libvirt in monitoring of virtual CPU and memory.
AbstractList Cloud computing is a new computing model. The resource monitoring tools are immature compared to traditional distributed computing and grid computing. In order to better monitor the virtual resource in cloud computing, a periodically and event-driven push (PEP) monitoring model is proposed. Taking advantage of the push and event-driven mechanism, the model can provide comparatively adequate information about usage and status of the resources. It can simplify the communication between Master and Work Nodes without missing the important issues happened during the push interval. Besides, we develop 'mon' to make up for the deficiency of Libvirt in monitoring of virtual CPU and memory.
TP3; Cloud computing is a new computing model.The resource monitoring tools are immature compared to traditional distributed computing and grid computing.In order to better monitor the virtual resource in cloud computing,a periodically and event-driven push(PEP)monitoring model is proposed.Taking advantage of the push and event-driven mechanism,the model can provide comparatively adequate information about usage and status of the resources.It can simplify the communication between Master and Work Nodes without missing the important issues happened during the push interval.Besides,we develop “mon” to make up for the deficiency of Libvirt in monitoring of virtual CPU and memory.
Cloud computing is a new computing model. The resource monitoring tools are immature compared to traditional distributed computing and grid computing. In order to better monitor the virtual resource in cloud computing, a periodically and event-driven push （PEP） monitoring model is proposed. Taking advantage of the push and event-driven mechanism, the model can provide comparatively adequate information about usage and status of the resources. It can simplify the communication between Master and Work Nodes without missing the important issues happened during the push interval. Besides, we develop ＂mon＂ to make up for the deficiency of Libvirt in monitoring of virtual CPU and memory.
Author 韩芳芳 彭俊杰 张武 李青 李建敦 江钦龙 袁勤
AuthorAffiliation School of Computer Engineering and Science, Shanghai University, Shanghai 200072, P. R. China Key Laboratory of Computer System and Architecture, Institute of Computing Technology, Chinese Academy of Science, Beijing 100190, P. R. China
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crossref_primary_10_1016_j_jpdc_2016_04_012
crossref_primary_10_1016_j_softx_2024_101675
crossref_primary_10_1016_j_ijleo_2016_04_114
crossref_primary_10_1016_j_sysarc_2014_01_009
Cites_doi 10.1109/SASO.2007.35
10.1016/j.future.2004.07.002
10.1016/j.parco.2004.04.001
10.1145/1165389.945462
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virtual resource monitoring
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Notes virtual resource monitoring, cloud computing, virtualization
HAN Fang-fang , PENG Jun-jie, ZHANG Wu , LI Qing 1, LI Jian-dun , JIANG Qin-long , YUAN Qin （1. School of Computer Engineering and Science, Shanghai University, Shanghai 200072, P. R. China ;2. Key Laboratory of Computer System and Architecture, Institute of Computing Technology, Chinese Academy of Science Beijing 100190, P. R. China）
Cloud computing is a new computing model. The resource monitoring tools are immature compared to traditional distributed computing and grid computing. In order to better monitor the virtual resource in cloud computing, a periodically and event-driven push （PEP） monitoring model is proposed. Taking advantage of the push and event-driven mechanism, the model can provide comparatively adequate information about usage and status of the resources. It can simplify the communication between Master and Work Nodes without missing the important issues happened during the push interval. Besides, we develop ＂mon＂ to make up for the deficiency of Libvirt in monitoring of virtual CPU and memory.
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– reference: Barham P, Dragovie B, Fraser K, Hand S, Harris T, Ho A, Neugebauer R, Pratt I, Warfield A. Xen and the art of virtualization [C]// Proceedings of the nineteenth ACM symposium on operating systems principles, New York, USA. 2003: 164–177.
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SubjectTerms Central processing units
Classical Mechanics
Cloud computing
Computation
Computational grids
Computer programs
Engineering
Environment
Information Technology
Intervals
Life Sciences
Materials Science
Mathematical and Computational Engineering
Mechatronics
Monitoring
Monitors
事件驱动机制
分布式计算
监控工具
监测模型
网格计算
虚拟资源
计算模型
资源监控
Title Virtual resource monitoring in cloud computing
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