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FleMA: A Flexible Measurement Architecture for ChinaGrid

  • Weimin Zheng
  • Meizhi Hu
  • Lin Liu
  • Yongwei Wu
  • Jing Tie
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3759)

Abstract

Grid technologies are becoming more and more mature in recent years. In contrast to this trend, the resource measurement landscape in Grids looks rather dismal. As part of ChinaGrid SuperVision project, a Flexible Measurement Architecture (FleMA) for ChinaGrid is presented. In FleMA, business logic at application level is separated from the primary measurement issues at resource level to well adapt to various grid applications of ChinaGrid. A multi-level structure is exploited to generate compound metrics from raw measurements. FleMA also features open WSRF-compliant services and “plug-in” measurement pattern, making it possible to achieve and deploy advanced functions synchronously on top of the unique measurement substrate.

Keywords

Resource Level Business Logic Grid Application Advanced Function Measurement Pattern 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    Foster, I., Kesselman, C.: The Grid 2: Blueprint for a New Computing Infrastructure. Morgan Kaufmann Publishers Inc., San Francisco (2003)Google Scholar
  2. 2.
    ChinaGrid project, http://www.chinagrid.edu.cn
  3. 3.
    Jin, H.: ChinaGrid: Making grid computing a reality. In: Chen, Z., Chen, H., Miao, Q., Fu, Y., Fox, E., Lim, E.-p. (eds.) ICADL 2004. LNCS, vol. 3334, pp. 13–24. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  4. 4.
  5. 5.
    Web Services Distributed Management (WSDM), http://www.oasis-open.org/committees/tc_home.php?wg_abbrev=wsdm
  6. 6.
    R-GMA: Relational Grid Monitoring Architecture, http://www.r-gma.org
  7. 7.
    MDS: Monitoring Discovery System, http://www.globus.org/mds/
  8. 8.
    Wolski, R., Spring, N., Hayes, J.: The Network Weather Service: A Distributed Resource Performance Forecasting Service for Metacomputing. Future Generation Computing Systems 15, 757–768 (1999)CrossRefGoogle Scholar
  9. 9.
  10. 10.
    Java Message Service (JMS), http://java.sun.com/products/jms/
  11. 11.
  12. 12.
    Massie, M.L., Chun, B.N., Culler, D.E.: The Ganglia Distributed Monitoring System: Design, Implementation, and Experience. Parallel Computing 30(7) (July 2004)Google Scholar
  13. 13.
    Truong, H.-L., Fahringer, T.: SCALEA-G: A Unified Monitoring and Performance Analysis System for the Grid. Scientific Programming 12(4), 225–237 (2004)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Weimin Zheng
    • 1
  • Meizhi Hu
    • 1
  • Lin Liu
    • 1
  • Yongwei Wu
    • 1
  • Jing Tie
    • 2
  1. 1.Department of Computer Science and TechnologyTsinghua UniversityBeijingChina
  2. 2.Internet and Cluster Computing Center, College of ComputerHuazhong University of Science and TechnologyWuhanChina

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