Dynamic Connectivity in Disk Graphs

Authors Haim Kaplan, Alexander Kauer, Katharina Klost , Kristin Knorr , Wolfgang Mulzer , Liam Roditty, Paul Seiferth



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Author Details

Haim Kaplan
  • School of Computer Science, Tel Aviv University, Israel
Alexander Kauer
  • Institut für Informatik, Freie Universtiät Berlin, Germany
Katharina Klost
  • Institut für Informatik, Freie Universität Berlin, Germany
Kristin Knorr
  • Institut für Informatik, Freie Universität Berlin, Germany
Wolfgang Mulzer
  • Institut für Informatik, Freie Universität Berlin, Germany
Liam Roditty
  • Department of Computer Science, Bar Ilan University, Ramat Gan, Israel
Paul Seiferth
  • Institut für Informatik, Freie Universtiät Berlin, Germany

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Haim Kaplan, Alexander Kauer, Katharina Klost, Kristin Knorr, Wolfgang Mulzer, Liam Roditty, and Paul Seiferth. Dynamic Connectivity in Disk Graphs. In 38th International Symposium on Computational Geometry (SoCG 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 224, pp. 49:1-49:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)
https://doi.org/10.4230/LIPIcs.SoCG.2022.49

Abstract

Let S ⊆ ℝ² be a set of n planar sites, such that each s ∈ S has an associated radius r_s > 0. Let 𝒟(S) be the disk intersection graph for S. It has vertex set S and an edge between two distinct sites s, t ∈ S if and only if the disks with centers s, t and radii r_s, r_t intersect. Our goal is to design data structures that maintain the connectivity structure of 𝒟(S) as sites are inserted and/or deleted. First, we consider unit disk graphs, i.e., r_s = 1, for all s ∈ S. We describe a data structure that has O(log² n) amortized update and O(log n/log log n) amortized query time. Second, we look at disk graphs with bounded radius ratio Ψ, i.e., for all s ∈ S, we have 1 ≤ r_s ≤ Ψ, for a Ψ ≥ 1 known in advance. In the fully dynamic case, we achieve amortized update time O(Ψ λ₆(log n) log⁷ n) and query time O(log n/log log n), where λ_s(n) is the maximum length of a Davenport-Schinzel sequence of order s on n symbols. In the incremental case, where only insertions are allowed, we get logarithmic dependency on Ψ, with O(α(n)) query time and O(logΨ λ₆(log n) log⁷ n) update time. For the decremental setting, where only deletions are allowed, we first develop an efficient disk revealing structure: given two sets R and B of disks, we can delete disks from R, and upon each deletion, we receive a list of all disks in B that no longer intersect the union of R. Using this, we get decremental data structures with amortized query time O(log n/log log n) that support m deletions in O((nlog⁵ n + m log⁷ n) λ₆(log n) + nlog Ψ log⁴n) overall time for bounded radius ratio Ψ and O((nlog⁶ n + m log⁸n) λ₆(log n)) for arbitrary radii.

Subject Classification

ACM Subject Classification
  • Theory of computation → Computational geometry
  • Theory of computation → Data structures design and analysis
  • Mathematics of computing → Paths and connectivity problems
Keywords
  • Disk Graphs
  • Connectivity
  • Lower Envelopes

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References

  1. Pankaj K. Agarwal, Ravid Cohen, Dan Halperin, and Wolfgang Mulzer. Maintaining the union of unit discs under insertions with near-optimal overhead. In Proc. 35th Annu. Sympos. Comput. Geom. (SoCG), pages 26:1-26:15, 2019. URL: https://doi.org/10.4230/LIPIcs.SoCG.2019.26.
  2. Kevin Buchin, Maarten Löffler, Pat Morin, and Wolfgang Mulzer. Preprocessing imprecise points for Delaunay triangulation: Simplified and extended. Algorithmica, 61(3):674-693, 2011. URL: https://doi.org/10.1007/s00453-010-9430-0.
  3. Timothy M. Chan. Dynamic geometric data structures via shallow cuttings. Discrete Comput. Geom., 64(4):1235-1252, 2020. URL: https://doi.org/10.1007/s00454-020-00229-5.
  4. Timothy M. Chan, Mihai Pătraşcu, and Liam Roditty. Dynamic connectivity: Connecting to networks and geometry. SIAM J. Comput., 40(2):333-349, 2011. URL: https://doi.org/10.1137/090751670.
  5. Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, and Clifford Stein. Introduction to Algorithms. MIT Press, 3rd edition, 2009. Google Scholar
  6. David Eppstein, Giuseppe F Italiano, Roberto Tamassia, Robert E Tarjan, Jeffery Westbrook, and Moti Yung. Maintenance of a minimum spanning forest in a dynamic plane graph. J. Algorithms, 13(1):33-54, 1992. URL: https://doi.org/10.1016/0196-6774(92)90004-V.
  7. Sariel Har-Peled. Geometric Approximation Algorithms, volume 173. American Mathematical Society, 2011. URL: https://doi.org/10.1090/surv/173.
  8. Jacob Holm, Kristian de Lichtenberg, and Mikkel Thorup. Poly-logarithmic deterministic fully-dynamic algorithms for connectivity, minimum spanning tree, 2-edge, and biconnectivity. J. ACM, 48(4):723-760, 2001. URL: https://doi.org/10.1145/502090.502095.
  9. Haim Kaplan, Wolfgang Mulzer, Liam Roditty, Paul Seiferth, and Micha Sharir. Dynamic planar Voronoi diagrams for general distance functions and their algorithmic applications. Discrete Comput. Geom., 64(3):838-904, 2020. URL: https://doi.org/10.1007/s00454-020-00243-7.
  10. Chih-Hung Liu. Nearly optimal planar k nearest neighbors queries under general distance functions. In Proc. 31st Annu. ACM-SIAM Sympos. Discrete Algorithms (SODA), pages 2842-2859, 2020. URL: https://doi.org/10.1137/1.9781611975994.173.
  11. Micha Sharir and Pankaj K. Agarwal. Davenport-Schinzel sequences and their geometric applications. Cambridge University Press, 1995. Google Scholar
  12. Daniel D. Sleator and Robert Endre Tarjan. A data structure for dynamic trees. J. Comput. System Sci., 26(3):362-391, 1983. URL: https://doi.org/10.1016/0022-0000(83)90006-5.
  13. Mikkel Thorup. Near-optimal fully-dynamic graph connectivity. In Proc. 32nd Annu. ACM Sympos. Theory Comput. (STOC), pages 343-350, 2000. Google Scholar
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