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Large-Scale Resource Selection in Grids

  • Conference paper
On the Move to Meaningful Internet Systems 2004: OTM 2004 Workshops (OTM 2004)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3292))

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Abstract

Grid resource selection requires matching job requirements to available resources. This is a difficult problem when the number of attributes for each resource is large. We present an algorithm that uses the Singular Value Decomposition to encode each resource’s properties by a single value. Jobs are matched by using the same encoding to produce a value that can be rapidly compared to those of the resources. We show that reasonable matches can be found in time O(m log n) where n is the number of resources and m the number of attributes for which a job might have requirements. This is in contrast to “approximate nearest neighbor” techniques which require either time or storage exponential in m.

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Authors and Affiliations

  1. School of Computing, Queen’s University, Kingston, Canada

    Ali M. Roumani & David B. Skillicorn

Authors
  1. Ali M. Roumani
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  2. David B. Skillicorn
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Editor information

Editors and Affiliations

  1. Vrije Universiteit Brussel (VUB), STARLab, Bldg G/10, Pleinlaan 2, 1050, Brussels, Belgium

    Robert Meersman

  2. School of Computer Science and Information Technology, RMIT University, Bld 10.10, 376-392 Swanston Street, 3001, Melbourne, VIC, Australia

    Zahir Tari

  3. PrismTech, 4, Rue Angiboust, 91460, Marcoussis, France

    Angelo Corsaro

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© 2004 Springer-Verlag Berlin Heidelberg

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Roumani, A.M., Skillicorn, D.B. (2004). Large-Scale Resource Selection in Grids. In: Meersman, R., Tari, Z., Corsaro, A. (eds) On the Move to Meaningful Internet Systems 2004: OTM 2004 Workshops. OTM 2004. Lecture Notes in Computer Science, vol 3292. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30470-8_33

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  • DOI: https://doi.org/10.1007/978-3-540-30470-8_33

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-23664-1

  • Online ISBN: 978-3-540-30470-8

  • eBook Packages: Springer Book Archive

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