Reconfiguration of Information Management Framework Based on Adaptive Grid Computing

  • Eun-Ha Song
  • Sung-Kook Han
  • Laurence T. Yang
  • Young-Sik Jeong
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4330)


In this paper, GridIMF provides the users with consistency while adapting to variability grid information. GridIMF designs hierarchical 3-tier information management model in accordance with participating intention, roles and operating strategies of grid information. In order to manage grid information in effective ways, GridIMF provides grid service while dividing to GVMS and GRMS. GVMS suggests optimal virtual organization selection mechanism for improving performance of specific applications and LRM auto-recovery strategy that treat faults of virtual organization. GRMS supports adaptive performance-based task allocation method for load balancing and fault tolerance. State monitoring and visualization view provides adaptability of managing grid information. Application proxy removes inter-dependency between service objects of GridIMF and application objects. For analyzing GridIMF executability, it adapts two fractal image processing those characteristics are different.


Task Allocation Grid Resource Virtual Organization Grid Application Globus Toolkit 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Foster, I., Kesselman, C.: The Grid: Blueprint for a New Computing Infrastructure. Morgan Kaufmann, San Francisco (1999)Google Scholar
  2. 2.
    Foster, I., Kesselman, C., Tueche, S.: The Anatomy of the Grid: Enabling Scalable Virtual Organizations. International Journal Supercomputer Applications 15(3) (2001)Google Scholar
  3. 3.
    Foster, I.: The Grid: A New Infrastructure for 21st Century Science. Physics (2002)Google Scholar
  4. 4.
    Takefusa, A., Casanova, H., Matsuoka, S., Berman, F.: A Study of Deadline Scheduling for Client-Server Systems on the Computational Grid, High Performance Distributed Computing, 2001. In: Proceedings 10th IEEE International Symposium (August 2001)Google Scholar
  5. 5.
    Katzy, B.R.: Design and Implementation of Virtual Organizations. University St. Gallen and Erasmus University Rotterdam Google Scholar
  6. 6.
    Bajaj, R., Agrawal, D.P., Fellow: Improving Scheduling of Tasks in a Heterogeneous Environment. IEEE Trans. Parallel and Distributed Systems 15(2), 107–118 (2004)CrossRefGoogle Scholar
  7. 7.
    Buyya, R., Chapin, S., DiNucci, D.: Architectural Models for Resource Management in the Grid. In: Grid Computing GIRD 2000. First IEEE/ACM International Workshop, Bangalore, India, pp. 20–33 (2000)Google Scholar
  8. 8.
    Foster, I., Kesselman, C.: Globus: A Metacomputing Infrastructure Toolkit. International Journal supercomputer Applications 11(2), 115–128 (1997)CrossRefGoogle Scholar
  9. 9.
    Angulo, D., Foster, I., Liu, C., Yang, L.: Design and Evaluation of a Resource Selection Framework for Grid Applications. In: Proceedings of IEEE International Symposium on High Performance Distributed Computing (HPDC-11), Edinburgh, Scotland (July 2002)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Eun-Ha Song
    • 1
  • Sung-Kook Han
    • 1
  • Laurence T. Yang
    • 2
  • Young-Sik Jeong
    • 1
  1. 1.Department of Computer EngineeringWonkwang UniversityIksanKorea
  2. 2.Department of Computer ScienceSt. Francis Xavier UniversityAntigonishCanada

Personalised recommendations