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The effect of corners on the complexity of approximate range searching

Published:05 June 2006Publication History

ABSTRACT

Range searching is among the most fundamental problems in computational geometry. Given an n-element point set in Rd, the problem is to preprocess the points so that the total weight (or generally semigroup sum) of the points lying within a given query range η can be determined quickly. In the ε-approximate version we assume that η is bounded and we are to determine the semigroup sum of all the points contained within η and may additionally include any of the points lying within distance ε ⋅ diam(η) of η's boundary.In this paper we contrast the complexity of approximate range searching based on properties of the semigroup and range space. A semigroup (S,+) is idempotent if x + x = x for all xS, and it is integral if for all k ≥ 2, the k-fold sum x + … + x is not equal to x. Idempotence is important because points may be multiply counted, and this implies that generator subsets may overlap one another. Our recent results [Arya, Malamatos, Mount, "On the Importance of Idempotence," STOC 2006, to appear] imply that for approximate Euclidean-ball range searching, idempotence offers significant advantages. In particular, nearly matching upper and lower bounds show that the exponents in the ε-dependencies are roughly halved for idempotent semigroups.These prior results made critical use of two properties of Euclidean balls: smoothness and rotational symmetry. In this paper we consider two alternative formulations that arise from relaxing these properties. The first involves ranges with sharp corners and the second involves arbitrary smooth convex ranges. We show that, as with integrality, sharp corners have an adverse effect on the problem's complexity. We consider d-dimensional unit hypercube ranges under rigid motions. Assuming linear space, we show here that in the semigroup arithmetic model the worst-case query time assuming an arbitrary (possibly idempotent) faithful semigroup is Ω(1/εd−2√d). We further prove a tighter lower bound of Ω(1/εd−2 for the special case of integral semigroups. This nearly matches the best known upper bound of O(log n + (1/ε)d−1), which holds for arbitrary semigroups.In contrast, we show that the improvements offered by idempotence do apply to smooth convex ranges. We define a class of smooth convex ranges to have the property that at any boundary point of the range, it is possible to place a large Euclidean ball within the range that touches this point. We show that for smooth ranges and idempotent semigroups, ε-approximate range queries can be answered in O(log n + (1/ε)(d−1)/2 log (1/ε)) time using O(n/ε) space. We show that this is nearly tight by presenting a lower bound of Ω(log n + (1/ε)(d−1)/2). This bound is in the algebraic decision-tree model and holds irrespective of space.Our results show that, in contrast to exact range searching, the interplay of semigroup properties and the range space can result in dramatic differences in query times. This is born out through both upper and lower bounds.

References

  1. P. K. Agarwal and J. Erickson. Geometric range searching and its relatives. In B. Chazelle, J. E. Goodman, and R. Pollack, editors, Advances in Discrete and Computational Geometry, volume 223 of Contemporary Mathematics, pages 1--56. American Mathematical Society, Providence, RI, 1999.Google ScholarGoogle Scholar
  2. S. Arya and T. Malamatos. Linear-size approximate Voronoi diagrams. In Proc. 13th Annu. ACM-SIAM Sympos. Discrete Algorithms pages 147--155, 2002. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. S. Arya, T. Malamatos, and D. M. Mount. Space-efficient approximate Voronoi diagrams. In Proc. 34th Annu. ACM Sympos. Theory Comput., pages 721--730, 2002. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. S. Arya, T. Malamatos, and D. M. Mount. Space-time tradeoffs for approximate spherical range counting. In Proc. 16th Annu. ACM-SIAM Sympos. Discrete Algorithms, pages 535--544, 2005. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. S. Arya, T. Malamatos, and D. M. Mount. On the importance of idempotence. In Proc. 38th Annu. ACM Sympos. Theory Comput., 2006. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. S. Arya and D. M. Mount. Approximate range searching. Comput. Geom. Theory Appl., 17:135--152, 2000. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. I. Bárány. Intrinsic volumes and f-vectors of random polytopes. Math. Annalen, 285:671--699, 1989.Google ScholarGoogle ScholarCross RefCross Ref
  8. I. Bárány. The technique of M-regions and cap-coverings: A survey. In Proc. III International Conference in Stochastic Geometry, Convex Bodies and Empirical Measures, Part II, volume 65 of Rendi. del Circ. Matemat. di Palermo, pages 21--38, 2000.Google ScholarGoogle Scholar
  9. I. Bárány and D. Larman. Convex bodies, economic cap coverings, random polytopes. Mathematika, 35:274--291, 1988.Google ScholarGoogle ScholarCross RefCross Ref
  10. H. Brönnimann, B. Chazelle, and J. Pach. How hard is halfspace range searching. Discrete Comput. Geom., 10:143--155, 1993.Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. B. Chazelle. Lower bounds on the complexity of polytope range searching. J. Amer. Math. Soc., 2:637--666, 1989.Google ScholarGoogle ScholarCross RefCross Ref
  12. B. Chazelle, D. Liu, and A. Magen. Approximate range searching in higher dimension. In Proc. 16th Canad. Conf. Comput. Geom., pages 154--157, 2004.Google ScholarGoogle Scholar
  13. J. Erickson. Space-time tradeoffs for emptiness queries. SIAM J. Comput., 29:1968--1996, 2000. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. G. Ewald, D. G. Larman, and C. A. Rogers. The directions of the line segments and of the r-dimensional balls on the boundary of a convex body in Euclidean space. Mathematika, 17:1--20, 1970.Google ScholarGoogle ScholarCross RefCross Ref
  15. M. L. Fredman. Lower bounds on the complexity of some optimal data structures. SIAM J. Comput., 10:1--10, 1981.Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. J. Matoušek. Range searching with efficient hierarchical cuttings. Discrete Comput. Geom., 10(2):157--182, 1993.Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. J. Matoušek. Geometric range searching. ACM Comput. Surv., 26:421--461, 1994. Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. A. C. Yao. On the complexity of maintaining partial sums. SIAM J. Comput., 14:277--288, 1985.Google ScholarGoogle ScholarDigital LibraryDigital Library

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      cover image ACM Conferences
      SCG '06: Proceedings of the twenty-second annual symposium on Computational geometry
      June 2006
      500 pages
      ISBN:1595933409
      DOI:10.1145/1137856
      • Program Chairs:
      • Nina Amenta,
      • Otfried Cheong

      Copyright © 2006 ACM

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      Publication History

      • Published: 5 June 2006

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