Data Structures for Approximate Orthogonal Range Counting

  • Authors:
  • Yakov Nekrich

  • Affiliations:
  • Dept. of Computer Science, University of Bonn,

  • Venue:
  • ISAAC '09 Proceedings of the 20th International Symposium on Algorithms and Computation
  • Year:
  • 2009

Quantified Score

Hi-index 0.00

Visualization

Abstract

We present new data structures for approximately counting the number of points in an orthogonal range. There is a deterministic linear space data structure that supports updates in O(1) time and approximates the number of elements in a 1-D range up to an additive term k 1/c in O(loglogU·loglogn) time, where k is the number of elements in the answer, U is the size of the universe and c is an arbitrary fixed constant. We can estimate the number of points in a two-dimensional orthogonal range up to an additive term k ρ in O(loglogU + (1/ρ)loglogn) time for any ρ 0. We can estimate the number of points in a three-dimensional orthogonal range up to an additive term k ρ in O(loglogU + (loglogn)3 + (3 v )loglogn) time for $v=\log \frac{1}{\rho}/\log \frac{3}{2}+2$.