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Grid scheduling for interactive analysis.

Cécile Germain-Renaud1, Romain Texier, Angel Osorio

  • 1Laboratoire de Recherche en Informatique. cecile.germain@lri.fr

Studies in Health Technology and Informatics
|July 11, 2006
PubMed
Summary

Grids need to evolve from batch to interactive computing for pervasive computing. The EGEE grid can support this evolution with minor middleware changes, benefiting applications like medical imaging.

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Area of Science:

  • Computer Science
  • Distributed Computing
  • Grid Computing

Background:

  • The evolution of computing systems from batch processing to interactive environments.
  • The emergence of pervasive and ubiquitous computing paradigms.
  • The current state of grid computing infrastructure and its limitations.

Purpose of the Study:

  • To assess the EGEE (Enabling Grids for E-sciencE) grid's readiness for interactive computing.
  • To identify necessary middleware evolutions for supporting interactive workloads.
  • To highlight the specific requirements of ultra-short jobs in grid environments.

Main Methods:

  • Analysis of EGEE's existing services and middleware.
  • Evaluation of EGEE's suitability for interactive computing tasks.

Related Experiment Videos

  • Case study using medical image analysis to define job requirements.

    • Main Results:

    • EGEE currently lacks the necessary services for interactive computing.
    • The EGEE grid architecture is adaptable to interactive computing through modest middleware enhancements.
    • Medical image analysis presents unique challenges for ultra-short jobs on grids.

    Conclusions:

    • Grids, exemplified by EGEE, must transition to interactive computing to enable ambient intelligence and ubiquitous computing.
    • Relatively small middleware modifications can equip EGEE for interactive workloads.
    • Addressing the needs of ultra-short jobs is crucial for grid evolution.