Four-Dimensional Dominance Range Reporting in Linear Space

Author Yakov Nekrich



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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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References

  1. Peyman Afshani. On dominance reporting in 3d. In Proc. 16th Annual European Symposium on Algorithms (ESA), pages 41-51, 2008. Google Scholar
  2. Peyman Afshani, Timothy M. Chan, and Konstantinos Tsakalidis. Deterministic rectangle enclosure and offline dominance reporting on the RAM. In Proceedings of 41st International Colloquium on Automata, Languages, and Programming (ICALP), pages 77-88, 2014. URL: https://doi.org/10.1007/978-3-662-43948-7_7.
  3. Pankaj K. Agarwal. Range searching. In Jacob E. Goodman and Joseph O'Rourke, editors, Handbook of Discrete and Computational Geometry, Second Edition., pages 809-837. Chapman and Hall/CRC, 2004. URL: https://doi.org/10.1201/9781420035315.ch36.
  4. Pankaj K. Agarwal and Jeff Erickson. Geometric range searching and its relatives. Contemporary Mathematics, 223:1-56, 1999. Google Scholar
  5. Stephen Alstrup, Gerth Stølting Brodal, and Theis Rauhe. New data structures for orthogonal range searching. In Proc. 41st Annual Symposium on Foundations of Computer Science, (FOCS), pages 198-207, 2000. URL: https://doi.org/10.1109/SFCS.2000.892088.
  6. Stephen Alstrup, Gerth Stølting Brodal, and Theis Rauhe. Optimal static range reporting in one dimension. In Proc. 33rd Annual ACM Symposium on Theory of Computing (STOC), pages 476-482, 2001. URL: https://doi.org/10.1145/380752.380842.
  7. Jon Louis Bentley. Multidimensional divide-and-conquer. Communications of the ACM, 23(4):214-229, 1980. URL: https://doi.org/10.1145/358841.358850.
  8. Jon Louis Bentley and Hermann A. Maurer. Efficient worst-case data structures for range searching. Acta Inf., 13:155-168, 1980. URL: https://doi.org/10.1007/BF00263991.
  9. Timothy M. Chan. Persistent predecessor search and orthogonal point location on the word RAM. In Proc. 22nd Annual ACM-SIAM Symposium on Discrete Algorithms (SODA), pages 1131-1145, 2011. URL: https://doi.org/10.1137/1.9781611973082.85.
  10. Timothy M. Chan. Persistent predecessor search and orthogonal point location on the word RAM. ACM Transactions on Algorithms, 9(3):22:1-22:22, 2013. URL: https://doi.org/10.1145/2483699.2483702.
  11. Timothy M. Chan, Kasper Green Larsen, and Mihai Patrascu. Orthogonal range searching on the RAM, revisited. In Proc. 27th ACM Symposium on Computational Geometry, (SoCG), pages 1-10, 2011. Google Scholar
  12. Bernard Chazelle. Filtering search: a new approach to query-answering. SIAM Journal on Computing, 15(3):703-724, 1986. URL: https://doi.org/10.1137/0215051.
  13. Bernard Chazelle. A functional approach to data structures and its use in multidimensional searching. SIAM Journal on Computing, 17(3):427-462, 1988. Preliminary version in FOCS 1985. Google Scholar
  14. Bernard Chazelle. Lower bounds for orthogonal range searching: I. the reporting case. J. ACM, 37(2):200-212, 1990. URL: https://doi.org/10.1145/77600.77614.
  15. Bernard Chazelle. Lower bounds for orthogonal range searching II. the arithmetic model. J. ACM, 37(3):439-463, 1990. URL: https://doi.org/10.1145/79147.79149.
  16. Bernard Chazelle and Herbert Edelsbrunner. Linear space data structures for two types of range search. Discrete & Computational Geometry, 2:113-126, 1987. Preliminary version in SoCG 1986. URL: https://doi.org/10.1007/BF02187875.
  17. Bernard Chazelle and Leonidas J. Guibas. Fractional cascading: I. A data structuring technique. Algorithmica, 1(2):133-162, 1986. URL: https://doi.org/10.1007/BF01840440.
  18. Bernard Chazelle and Leonidas J. Guibas. Fractional cascading: II. applications. Algorithmica, 1(2):163-191, 1986. URL: https://doi.org/10.1007/BF01840441.
  19. Arash Farzan, J. Ian Munro, and Rajeev Raman. Succinct indices for range queries with applications to orthogonal range maxima. In Proc. 39th International Colloquium on Automata, Languages, and Programming (ICALP), pages 327-338, 2012. URL: https://doi.org/10.1007/978-3-642-31594-7_28.
  20. Roberto Grossi, Alessio Orlandi, Rajeev Raman, and S. Srinivasa Rao. More haste, less waste: Lowering the redundancy in fully indexable dictionaries. In Proc. 26th International Symposium on Theoretical Aspects of Computer Science, (STACS), pages 517-528, 2009. URL: https://doi.org/10.4230/LIPIcs.STACS.2009.1847.
  21. Joseph JáJá, Christian Worm Mortensen, and Qingmin Shi. Space-efficient and fast algorithms for multidimensional dominance reporting and counting. In Proc. 15th International Symposium on Algorithms and Computation (ISAAC), pages 558-568, 2004. URL: https://doi.org/10.1007/978-3-540-30551-4_49.
  22. Marek Karpinski and Yakov Nekrich. Space efficient multi-dimensional range reporting. In Proc. 15th Annual International Conference on Computing and Combinatorics (COCOON), pages 215-224, 2009. URL: https://doi.org/10.1007/978-3-642-02882-3_22.
  23. George S. Lueker. A data structure for orthogonal range queries. In Proc. 19th Annual Symposium on Foundations of Computer Science (FOCS), pages 28-34, 1978. URL: https://doi.org/10.1109/SFCS.1978.1.
  24. Edward M. McCreight. Priority search trees. SIAM Journal on Computing, 14(2):257-276, 1985. URL: https://doi.org/10.1137/0214021.
  25. Yakov Nekrich. A data structure for multi-dimensional range reporting. In Proc. 23rd ACM Symposium on Computational Geometry (SoCG), pages 344-353, 2007. URL: https://doi.org/10.1145/1247069.1247130.
  26. Yakov Nekrich. External memory range reporting on a grid. In Proc. 18th International Symposium on Algorithms and Computation (ISAAC), pages 525-535, 2007. URL: https://doi.org/10.1007/978-3-540-77120-3_46.
  27. Yakov Nekrich. Space efficient dynamic orthogonal range reporting. Algorithmica, 49(2):94-108, 2007. URL: https://doi.org/10.1007/s00453-007-9030-9.
  28. Yakov Nekrich. Orthogonal range searching in linear and almost-linear space. Computational Geometry: Theory & Applications, 42(4):342-351, 2009. URL: https://doi.org/10.1016/j.comgeo.2008.09.001.
  29. Yakov Nekrich. Orthogonal range searching on discrete grids. In Encyclopedia of Algorithms, pages 1484-1489. Springer, New York, 2016. URL: https://doi.org/10.1007/978-1-4939-2864-4_631.
  30. Yakov Nekrich. Four-dimensional dominance range reporting in linear space. CoRR, abs/2003.06742, 2020. URL: http://arxiv.org/abs/2003.06742.
  31. Yakov Nekrich and Gonzalo Navarro. Sorted range reporting. In Proc. 13th Scandinavian Symposium and Workshops on Algorithm Theory (SWAT), pages 271-282, 2012. URL: https://doi.org/10.1007/978-3-642-31155-0_24.
  32. Mark H. Overmars. Efficient data structures for range searching on a grid. J. Algorithms, 9(2):254-275, 1988. URL: https://doi.org/10.1016/0196-6774(88)90041-7.
  33. Mihai Patrascu. Unifying the landscape of cell-probe lower bounds. SIAM J. Comput., 40(3):827-847, 2011. URL: https://doi.org/10.1137/09075336X.
  34. Sairam Subramanian and Sridhar Ramaswamy. The P-range tree: A new data structure for range searching in secondary memory. In Proc. 6th Annual ACM-SIAM Symposium on Discrete Algorithms (SODA), pages 378-387, 1995. Google Scholar
  35. Darren Erik Vengroff and Jeffrey Scott Vitter. Efficient 3-d range searching in external memory. In Proc. 28th Annual ACM Symposium on the Theory of Computing (STOC), pages 192-201, 1996. Google Scholar
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