PIVOT: An adaptive information discovery framework for computational grids

Guiyi Wei, Yun Ling, Athanasios V. Vasilakos, Bin Xiao, Yao Zheng

Research output: Journal article publicationJournal articleAcademic researchpeer-review

8 Citations (Scopus)

Abstract

In a traditional computational grid environment, the owners of resources usually provide information about their resources extracted by pre-configured information services or web services. However, such information is not sufficient for the scheduler in the high-performance distributed computing. To solve this problem, we propose a scalable grid information service framework, named PIVOT (adaPtive Information discoVery framewOrk for compuTational grid). By using deadline-constrained flooding collector dissemination and P2P-like information collection schemes, PIVOT provides an active mechanism to collect application-specific resource information. In particular, PIVOT provides a resource information service for application-specific schedulers. The best-effort performance on overhead traffic and communication latency during information discovery is guaranteed by two new distributed cooperative algorithms. The experimental results in the simulations and real computational grid platform demonstrate that PIVOT has a high level of adaptability for application-specific resource information discovery, and also improves the accuracy of resource allocation and the efficiency of executing parallel tasks in traditional information services.
Original languageEnglish
Pages (from-to)4543-4556
Number of pages14
JournalInformation Sciences
Volume180
Issue number23
DOIs
Publication statusPublished - 1 Dec 2010

Keywords

  • Adaptiveness
  • Computational grid
  • Distributed cooperation
  • Information discovery
  • Resource scheduling
  • Scalability

ASJC Scopus subject areas

  • Software
  • Control and Systems Engineering
  • Theoretical Computer Science
  • Computer Science Applications
  • Information Systems and Management
  • Artificial Intelligence

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