AI Clustering Techniques : a New Approach to Object Oriented Database Fragmentation

@inproceedings{Darabant2004AICT,
  title={AI Clustering Techniques : a New Approach to Object Oriented Database Fragmentation},
  author={Adrian Sergiu Darabant and Alina Campan},
  year={2004}
}
Optimal application performance on a Distributed Object Based System requires class fragmentation and the development of allocation schemes to place fragments at distributed sites so data transfer is minimal. In this paper we present a horizontal fragmentation approach that uses the k-means centroid based clustering method for partitioning object instances into fragments. Our new method takes full advantage of existing data, where statistics are already present. We model fragmentation input… CONTINUE READING

References

Publications referenced by this paper.
Showing 1-10 of 12 references

Hierarchical AI Clustering for Horizontal Object Fragmentation

  • A. S. Darabant, Campan
  • Proc of Int. Conf. of Computers and…
  • 2004
Highly Influential
3 Excerpts

La fragmentation d’un schema conceptuel oriente objet

  • S. Ravat
  • In Ingenierie des systemes d’information (ISI),
  • 1996
1 Excerpt

Structural Schema Information as Heuristics for Horizontal Fragmentation of Object Classes in Distributed OODB

  • Savonnet, M. et. al
  • In Proc IX Int. Conf. on Parallel and Distributed…
  • 1996
1 Excerpt

– “ Using Structural Schema Information as Heuristics for Horizontal Fragmentation of Object Classes in Distributed OODB ”

  • F. Baiao, M. Mattoso
  • 1996

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