Research Article

e-Business applications on the Grid: a toolkit for centralized workload prediction and access

  1. Konstantinos Dolkas3,*,
  2. Dimosthenis Kyriazis1,
  3. Andreas Menychtas1,
  4. Theodora Varvarigou1

Article first published online: 10 OCT 2006

DOI: 10.1002/cpe.1093

Issue

Concurrency and Computation: Practice and Experience

Concurrency and Computation: Practice and Experience

Special Issue: Science Gateways—Common Community Interfaces to Grid Resources

Volume 19, Issue 6, pages 867–883, 25 April 2007

Additional Information

How to Cite

Dolkas, K., Kyriazis, D., Menychtas, A. and Varvarigou, T. (2007), e-Business applications on the Grid: a toolkit for centralized workload prediction and access. Concurrency Computat.: Pract. Exper., 19: 867–883. doi: 10.1002/cpe.1093

Author Information

  1. 1

    Telecommunications Laboratory, Department of Electrical and Computer Engineering, National Technical University of Athens, 9 Heroon Polytechniou Street, 15773 Zografou Campus, Athens, Greece

  2. 3

    San Diego Supercomputer Center, University of California at San Diego, La Jolla, CA, U.S.A.

*Telecommunications Laboratory, Department of Electrical and Computer Engineering, National Technical University of Athens, 9 Heroon Polytechniou Street, 15773 Zografou Campus, Athens, Greece

Publication History

  1. Issue published online: 13 MAR 2007
  2. Article first published online: 10 OCT 2006
  3. Manuscript Accepted: 9 MAY 2006
  4. Manuscript Revised: 5 APR 2006
  5. Manuscript Received: 15 AUG 2005

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Keywords:

  • Grid computing;
  • Grid toolkit;
  • workload prediction;
  • centralized access

Abstract

Enabling e-Business applications on Grid computing has been an important topic of research as the beneficial perspective of Grids lies on solving computational intensive problems by large-scale distributed resources. In this paper we present a toolkit for centralized workload prediction and access, in order to meet the requirements of execution of commercial business processes on Grid infrastructures as well as to take advantage of their cost-effective capability for industrial users. The implementation of centralized workload prediction is achieved with an artificial neural network—available in the toolkit—each time a user completes a job execution. This approach has been adopted and validated within the framework of a GRIA IST project for aspecific industrial application, namely 3D image rendering, which meets the e-Business application's standards. The accuracy of the prediction showed promising results and in combination with the centralized access capability makes e-Business applications feasible on Grids. Copyright © 2006 John Wiley & Sons, Ltd.

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