Data Intensive Grid Scheduling: Multiple Sources with Capacity Constraints

Han Min Wong, Bharadwaj Veeravalli, Dantong Yu, Thomas G. Robertazzi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

31 Scopus citations

Abstract

In this paper, we apply divisible load theory to model the Grid scheduling problem involving multiple sources to multiple sinks, and present an optimized scheduling technique for this scenario. This scheduling technique can be easily extended to schedule resources with buffer space constraints. We provide a step-wise scheduling algorithm for these constraints. Two example calculations will show the practical utility and efficiency of DLT.

Original languageEnglish (US)
Title of host publicationProceedings of the Fifteenth IASTED International Conference on Parallel and Distributed Computing and Sytems
EditorsT. Gonzalez
Pages7-11
Number of pages5
Edition1
StatePublished - Dec 1 2003
Externally publishedYes
EventProceedings of the Fifteenth IASTED International Conference on Parallel and Distributed Computing and Systems - Marina del Rey, CA, United States
Duration: Nov 3 2003Nov 5 2003

Publication series

NameProceedings of the IASTED International Conference on Parallel and Distributed Computing and Systems
Number1
Volume15

Other

OtherProceedings of the Fifteenth IASTED International Conference on Parallel and Distributed Computing and Systems
CountryUnited States
CityMarina del Rey, CA
Period11/3/0311/5/03

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All Science Journal Classification (ASJC) codes

  • Software
  • Hardware and Architecture
  • Computer Networks and Communications

Keywords

  • Divisible load scheduling theory(DLT)
  • Grid computing
  • Heterogeneous computing
  • Parallel computing
  • Resource constraints

Cite this

Wong, H. M., Veeravalli, B., Yu, D., & Robertazzi, T. G. (2003). Data Intensive Grid Scheduling: Multiple Sources with Capacity Constraints. In T. Gonzalez (Ed.), Proceedings of the Fifteenth IASTED International Conference on Parallel and Distributed Computing and Sytems (1 ed., pp. 7-11). (Proceedings of the IASTED International Conference on Parallel and Distributed Computing and Systems; Vol. 15, No. 1).