License: Creative Commons Attribution 4.0 International license (CC BY 4.0)
When quoting this document, please refer to the following
DOI: 10.4230/LIPIcs.ICDT.2023.21
URN: urn:nbn:de:0030-drops-177624
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2023/17762/
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Meng, Jingfan ; Wang, Huayi ; Xu, Jun ; Ogihara, Mitsunori

On Efficient Range-Summability of IID Random Variables in Two or Higher Dimensions

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LIPIcs-ICDT-2023-21.pdf (1.0 MB)

Abstract

d-dimensional (for d > 1) efficient range-summability (dD-ERS) of random variables (RVs) is a fundamental algorithmic problem that has applications to two important families of database problems, namely, fast approximate wavelet tracking (FAWT) on data streams and approximately answering range-sum queries over a data cube. Whether there are efficient solutions to the dD-ERS problem, or to the latter database problem, have been two long-standing open problems. Both are solved in this work. Specifically, we propose a novel solution framework to dD-ERS on RVs that have Gaussian or Poisson distribution. Our dD-ERS solutions are the first ones that have polylogarithmic time complexities. Furthermore, we develop a novel k-wise independence theory that allows our dD-ERS solutions to have both high computational efficiencies and strong provable independence guarantees. Finally, we show that under a sufficient and likely necessary condition, certain existing solutions for 1D-ERS can be generalized to higher dimensions.

BibTeX - Entry

@InProceedings{meng_et_al:LIPIcs.ICDT.2023.21,
  author =	{Meng, Jingfan and Wang, Huayi and Xu, Jun and Ogihara, Mitsunori},
  title =	{{On Efficient Range-Summability of IID Random Variables in Two or Higher Dimensions}},
  booktitle =	{26th International Conference on Database Theory (ICDT 2023)},
  pages =	{21:1--21:18},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-270-9},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{255},
  editor =	{Geerts, Floris and Vandevoort, Brecht},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/opus/volltexte/2023/17762},
  URN =		{urn:nbn:de:0030-drops-177624},
  doi =		{10.4230/LIPIcs.ICDT.2023.21},
  annote =	{Keywords: fast range-summation, multidimensional data streams, Haar wavelet transform}
}

Keywords: fast range-summation, multidimensional data streams, Haar wavelet transform
Collection: 26th International Conference on Database Theory (ICDT 2023)
Issue Date: 2023
Date of publication: 17.03.2023

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