Reducing the Grid Monitoring Workload Using Application Characteristics Identification

您当前的位置：

首页 >

文章列表页 >

Reducing the Grid Monitoring Workload Using Application Characteristics Identification

更新时间：2025-07-09

- Reducing the Grid Monitoring Workload Using Application Characteristics Identification
- Vol. 43, Issue 8, Pages: 11-16(2009)
- 作者机构：
  
  西安交通大学电子与信息工程学院,西安,710049
- 作者简介：
- 基金信息：
- DOI：
  CLC： TP393
- Online First：10 August 2009，
  
  Published：2009
- 稿件说明：
移动端阅览
Reducing the Grid Monitoring Workload Using Application Characteristics Identification[J]. 2009, 43(8): 11-16.
DOI：

Reducing the Grid Monitoring Workload Using Application Characteristics Identification[J]. 2009, 43(8): 11-16. DOI：

摘要

针对网络监控负载随着监控任务的增加而增加

从而影响集群有效管理、利用及监控系统性能的问题

展开了利用应用程序特征识别降低网格监控负载的研究.采用主成分分析法分析程序执行过程中的监测数据

得到应用程序的主成分因子

再经由4种密集型基准程序构造的比对特征集合匹配

识别应用程序的主要特性

以此达到降低监控负载的目的.在原型系统上的应用程序特征识别及监控负载评估实验表明

对于混合类型应用程序或某种密集型应用程序

监控负载可以减少20%～60%

对于巨大的采集数据

可以做到有效精炼.

Abstract

The overhead of monitoring that increases with the increasing monitoring tasks is crucial to the effective management and efficient utilization of the cluster computers and to the performance of the monitoring system. Researches are made to reduce the overhead of monitoring by identifying the main characteristics of the application. Main factors of the application are dynamically identified by performing principal component analysis(PCA)on the fly of application execution. The set of the main characteristics is identified through matching up with the comparison characteristic set that is created by 4 categories resource intensive benchmark so that the monitoring workload is reduced. A prototype monitoring system adopting the proposed strategy is implemented. Experimental results show that the monitoring workload is decreased by 20% to 60% in hybrid applications or some resource intensive applications. Large collected data can be effectively refined and processed before inputting it to a monitoring system.

关键词

Keywords

references

王寅峰,董小社,何秀强,等.网格测试引擎:一种构建网格测试环境的基础架构[J].西安交通大学学报,2007, 41(8):884-888.

WANG Yinfeng, DONG Xiaoshe, HE Xiuqiang, et al. Grid testing engine: an infrastructure for constructing grid testing environment [J]. Journal of Xi'an Jiaotong University, 2007, 41(8), 884-888.

ZHANG Xuehai, FRESCHL J L, SCHOPF J M. A performance study of monitoring and information services for distributed systems [C]∥12th IEEE International Symposium on High Performance Distributed Computing. Los Alamitos, CA, USA: IEEE Computer Society,2003:270.

LIU Wei, LUO Tiejian, SONG Jinliang, et al. Improving grid monitoring with data quality assessment [C]∥International Symposium on Communications and Information Technologies. Los Alamitos, CA, USA:IEEE Computer Society,2007:1534-1539.

YOSHIKAZU K, KENJIRO T. Scalable data gathering for real-time monitoring systems on distributed computing[C]∥8th IEEE International Symposium on Cluster Computing and the Grid. Piscataway, NJ, USA: IEEE, 2008: 425-432.

YANG Lingyun, SCHOPF J M, DUMITRESCU C L, et al. Statistical data reduction for efficient application performance monitoring [C]∥Proceedings of the Grid Workshop. Los Alamitos, CA, USA: IEEE Computer Society,2006:327-334.

DUESTERWALD E, CASCAVAL C, DWARKADAS S. Characterizing and predicting program behavior and its variability [C]∥Proceedings of the 12th International Conference on Parallel Architectures and Compilation Techniques. Los Alamitos, CA, USA: IEEE Computer Society, 2003:220.

PHANSALKAR A, JOSHI A, EECKHOUT L, et al. Measuring program similarity: experiments with SPEC CPU benchmark suites [C]∥IEEE International Symposium on Performance Analysis of Systems and Software. Los Alamitos, CA, USA: IEEE Computer Society, 2005:10-20.

网格测试引擎:一种构建网格测试环境的基础架构. 西安交通大学学报,2007, 41(8):884-888.

考虑节点失效恢复能力的网格服务可靠性建模与分析. 西安交通大学学报, 2008, 42(6):693-697.

一种基于网关的网格数据互操作框架. 西安交通大学学报, 2009, 43(2):20-24.

八邻域网格聚类的多样性XML文档近似查询算法. 西安交通大学学报, 2007, 41(8):907-911.

Views

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Uncertainty Quantification Method on the Influence of Global Blade Twist Angle Errors on Axial Compressor Performance

Real-Time Removal of Ocular Artifacts from EEG Signals Using ICA and Manifold Algorithm

A Probabilistic Principal Component Analysis Approach for Detecting Traffic Anomaly in Industrial Networks

Modal Parameter Identification with Principal Component Analysis

A Fast Determination Algorithm for Slicing Direction of 3D Printing

Related Author

SHEN Yihao

MO Yuqin

LIU Kaiye

CHU Wuli

ZHAI Yichen

王沛

郑崇勋

高军峰

Related Institution

School of Power and Energy, Northwestern Polytechnical University

School of Life Sciences and Technology, Xi'an Jiaotong University

College of Electric and Information Engineering, Naval University of Engineering

College of Computer Science and Technology, Huaqiao University

State Key Laboratory for Strength and Vibration of Mechanical Structures, Xi'an Jiaotong University

⁰