A Two Level Approach for Managing Resource and Data Intensive Tasks in Grids

  • Authors:
  • Imran Ahmad;Shikharesh Majumdar

  • Affiliations:
  • Department of Systems and Computer Engineering, Carleton University, Ottawa, Canada;Department of Systems and Computer Engineering, Carleton University, Ottawa, Canada

  • Venue:
  • OTM '08 Proceedings of the OTM 2008 Confederated International Conferences, CoopIS, DOA, GADA, IS, and ODBASE 2008. Part I on On the Move to Meaningful Internet Systems:
  • Year:
  • 2008

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Abstract

In recent years, Grid computing has emerged as an attractive platform to tackle various large-scale problems, especially in the field of science and engineering. Scheduling Grid resources involves a number of challenging issues, mainly due to the distributed and dynamic nature of the Grids. This paper focuses on the resource allocation for a particular type of resource intensive tasks called Processable Bulk Data Transfer (PBDT) tasks in a Grid environment. The defining trait of a PBDT task is a large raw data-file at a source node that needs to be processed in some way before it can be used at a set of sink nodes. Our scheduling approach uses a Bi-level decision-making architecture. This paper analyzes the performance of the proposed architecture at various workload conditions. This architecture can be extended for other types of tasks using the concepts presented.