Research Article

Ontology-based Grid resource management

  1. Balachandar R. Amarnath1,*,
  2. Thamarai Selvi Somasundaram1,
  3. Mahendran Ellappan1,
  4. Rajkumar Buyya2

Article first published online: 27 OCT 2009

DOI: 10.1002/spe.942

Issue

Software: Practice and Experience

Software: Practice and Experience

Volume 39, Issue 17, pages 1419–1438, 10 December 2009

Additional Information

How to Cite

Amarnath, B. R., Somasundaram, T. S., Ellappan, M. and Buyya, R. (2009), Ontology-based Grid resource management. Software: Practice and Experience, 39: 1419–1438. doi: 10.1002/spe.942

Author Information

  1. 1

    CARE, Department of Information Technology, Madras Institute of Technology, Anna University Chennai, Chromepet, Chennai 600 044, India

  2. 2

    Cloud Computing and Distributed Systems Laboratory, Department of Computer Science and Software Engineering, The University of Melbourne, VIC 3010, Australia

*CARE, Department of Information Technology, Madras Institute of Technology, Anna University Chennai, Chromepet, Chennai 600 044, India

Publication History

  1. Issue published online: 29 OCT 2009
  2. Article first published online: 27 OCT 2009
  3. Manuscript Accepted: 2 SEP 2009
  4. Manuscript Revised: 28 AUG 2009
  5. Manuscript Received: 9 JUN 2009

Funded by

  • Ministry of Communication and Information Technology, Government of India
  • Australian Department of Innovation, Industry, Science and Research

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Keywords:

  • Grid computing;
  • semantic Grid;
  • ontology;
  • Grid resource;
  • management

Abstract

Grid resources are typically diverse in nature with respect to their software and hardware configurations, resource usage policies and the kind of application they support. Aggregating and monitoring these resources, and discovering suitable resources for the applications become a challenging issue. This is partially due to the representation of Grid metadata supported by the existing Grid middleware which offers limited scope for matching the job requirements that directly affect scheduling decisions. This paper proposes a semantic component in conventional Grid architecture to support ontology-based representation of Grid metadata and facilitate context-based information retrieval that complements Grid schedulers for effective resource management. Web Ontology language is used for creating Grid resource ontology and Algernon inference engine has been used for resource discovery. This semantic component has been integrated with conventional Grid schedulers. Several experiments have also been carried out to investigate the performance overhead that arises while integrating this component with Grid schedulers. Copyright © 2009 John Wiley & Sons, Ltd.

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