Local grid scheduling techniques using performance prediction

D. P. Spooner*, S. A. Jarvis, J. Cao, S. Saini, G. R. Nudd

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

110 Citations (Scopus)


The use of computational grids to provide an integrated computer platform, composed of differentiated and distributed systems, presents fundamental resource and workload management questions. Key services such as resource discovery, monitoring and scheduling are inherently more complicated in a grid environment where the resource pool is large, dynamic and architecturally diverse. The authors approach the problem of grid workload management through the development of a multi-tiered scheduling architecture (TITAN) that employs a performance prediction system (PACE) and task distribution brokers to meet user-defined deadlines and improve resource usage efficiency. Attention is focused on the lowest tier which is responsible for local scheduling. By coupling application performance data with scheduling heuristics, the architecture is able to balance the processes of minimising run-to-completion time and processor idle time, whilst adhering to service deadlines on a per-task basis.

Original languageEnglish
Pages (from-to)87-96
Number of pages10
JournalIEE Proceedings: Computers and Digital Techniques
Issue number2
Publication statusPublished - Mar 2003

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Hardware and Architecture
  • Computational Theory and Mathematics


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