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Four-Dimensional Dominance Range Reporting in Linear Space

Author Yakov Nekrich



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LIPIcs.SoCG.2020.59.pdf
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Yakov Nekrich
  • Department of Computer Science, Michigan Technological University, Houghton, MI, USA

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Yakov Nekrich. Four-Dimensional Dominance Range Reporting in Linear Space. In 36th International Symposium on Computational Geometry (SoCG 2020). Leibniz International Proceedings in Informatics (LIPIcs), Volume 164, pp. 59:1-59:14, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2020)
https://doi.org/10.4230/LIPIcs.SoCG.2020.59

Abstract

In this paper we study the four-dimensional dominance range reporting problem and present data structures with linear or almost-linear space usage. Our results can be also used to answer four-dimensional queries that are bounded on five sides. The first data structure presented in this paper uses linear space and answers queries in O(log^{1+ε} n + k log^ε n) time, where k is the number of reported points, n is the number of points in the data structure, and ε is an arbitrarily small positive constant. Our second data structure uses O(n log^ε n) space and answers queries in O(log n+k) time. These are the first data structures for this problem that use linear (resp. O(n log^ε n)) space and answer queries in poly-logarithmic time. For comparison the fastest previously known linear-space or O(n log^ε n)-space data structure supports queries in O(n^ε + k) time (Bentley and Mauer, 1980). Our results can be generalized to d ≥ 4 dimensions. For example, we can answer d-dimensional dominance range reporting queries in O(log log n (log n/log log n)^{d-3} + k) time using O(n log^{d-4+ε} n) space. Compared to the fastest previously known result (Chan, 2013), our data structure reduces the space usage by O(log n) without increasing the query time.

Subject Classification

ACM Subject Classification
  • Theory of computation → Computational geometry
  • Theory of computation → Data structures design and analysis
Keywords
  • Range searching
  • geometric data structures
  • word RAM

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