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Performance evaluation for clustering algorithms in object-oriented database systems

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Database and Expert Systems Applications (DEXA 1995)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 978))

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Abstract

It is widely acknowledged that good object clustering is critical to the performance of object-oriented databases. However, object clustering always involves some kind of overhead for the system. The aim of this paper is to propose a modelling methodology in order to evaluate the performances of different clustering policies. This methodology has been used to compare the performances of three clustering algorithms found in the literature (Cactis, CK and ORION) that we considered representative of the current research in the field of object clustering. The actual performance evaluation was performed using simulation. Simulation experiments we performed showed that the Cactis algorithm is better than the ORION algorithm and that the CK algorithm totally outperforms both other algorithms in terms of response time and clustering overhead.

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Authors and Affiliations

  1. Laboratoire d'Informatique, Complexe scientifique des Cézeaux, Université Blaise Pascal-Clermont-Ferrand II, 63177, Aubière Cedex, France

    Jérôme Darmont, Ammar Attoui & Michel Gourgand

Authors
  1. Jérôme Darmont
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  2. Ammar Attoui
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  3. Michel Gourgand
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Editor information

Norman Revell A Min Tjoa

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© 1995 Springer-Verlag Berlin Heidelberg

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Darmont, J., Attoui, A., Gourgand, M. (1995). Performance evaluation for clustering algorithms in object-oriented database systems. In: Revell, N., Tjoa, A.M. (eds) Database and Expert Systems Applications. DEXA 1995. Lecture Notes in Computer Science, vol 978. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0049117

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  • DOI: https://doi.org/10.1007/BFb0049117

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-60303-0

  • Online ISBN: 978-3-540-44790-0

  • eBook Packages: Springer Book Archive

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