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Frontiers of Computer Science

, Volume 6, Issue 2, pp 166–178 | Cite as

Resilient k-d trees: k-means in space revisited

  • Fabian GiesekeEmail author
  • Gabriel Moruz
  • Jan Vahrenhold
Research Article
  • 82 Downloads

Abstract

We propose a k-d tree variant that is resilient to a pre-described number of memory corruptions while still using only linear space. While the data structure is of independent interest, we demonstrate its use in the context of high-radiation environments. Our experimental evaluation demonstrates that the resulting approach leads to a significantly higher resiliency rate compared to previous results. This is especially the case for large-scale multi-spectral satellite data, which renders the proposed approach well-suited to operate aboard today’s satellites.

Keywords

data mining clustering resilient algorithms and data structures 

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Copyright information

© Higher Education Press and Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  1. 1.Department für InformatikCarl von Ossietzky Universität OldenburgOldenburgGermany
  2. 2.Department of Computer ScienceGoethe Universität Frankfurt am MainFrankfurt am MainGermany
  3. 3.Fakultät für InformatikTechnische Universität DortmundDortmundGermany

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