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Fully Dynamic Maximum Independent Sets of Disks in Polylogarithmic Update Time

Authors Sujoy Bhore , Martin Nöllenburg , Csaba D. Tóth , Jules Wulms

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Author Details

Sujoy Bhore
  • Department of Computer Science and Engineering, Indian Institute of Technology Bombay, Mumbai, India
Martin Nöllenburg
  • Institute of Logic and Computation, Algorithms and Complexity Group, TU Wien, Austria
Csaba D. Tóth
  • Department of Mathematics, California State University Northridge, Los Angeles, CA, USA
  • Department of Computer Science, Tufts University, Medford, MA, USA
Jules Wulms
  • Department of Mathematics and Computer Science, TU Eindhoven, The Netherlands

Funding

  • Tóth, Csaba D.: Research was partially supported by the NSF award DMS-2154347.

Cite AsGet BibTex

Sujoy Bhore, Martin Nöllenburg, Csaba D. Tóth, and Jules Wulms. Fully Dynamic Maximum Independent Sets of Disks in Polylogarithmic Update Time. In 40th International Symposium on Computational Geometry (SoCG 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 293, pp. 19:1-19:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)
https://doi.org/10.4230/LIPIcs.SoCG.2024.19

Abstract

A fundamental question is whether one can maintain a maximum independent set (MIS) in polylogarithmic update time for a dynamic collection of geometric objects in Euclidean space. For a set of intervals, it is known that no dynamic algorithm can maintain an exact MIS in sublinear update time. Therefore, the typical objective is to explore the trade-off between update time and solution size. Substantial efforts have been made in recent years to understand this question for various families of geometric objects, such as intervals, hypercubes, hyperrectangles, and fat objects. We present the first fully dynamic approximation algorithm for disks of arbitrary radii in the plane that maintains a constant-factor approximate MIS in polylogarithmic expected amortized update time. Moreover, for a fully dynamic set of n unit disks in the plane, we show that a 12-approximate MIS can be maintained with worst-case update time O(log n), and optimal output-sensitive reporting. This result generalizes to fat objects of comparable sizes in any fixed dimension d, where the approximation ratio depends on the dimension and the fatness parameter. Further, we note that, even for a dynamic set of disks of unit radius in the plane, it is impossible to maintain O(1+ε)-approximate MIS in truly sublinear update time, under standard complexity assumptions. Our results build on two recent technical tools: (i) The MIX algorithm by Cardinal et al. (ESA 2021) that can smoothly transition from one independent set to another; hence it suffices to maintain a family of independent sets where the largest one is an O(1)-approximate MIS. (ii) A dynamic nearest/farthest neighbor data structure for disks by Kaplan et al. (DCG 2020) and Liu (SICOMP 2022), which generalizes the dynamic convex hull data structure by Chan (JACM 2010), and quickly yields a "replacement" disk (if any) when a disk in one of our independent sets is deleted.

Subject Classification

ACM Subject Classification
  • Theory of computation → Computational geometry
Keywords
  • Dynamic algorithm
  • Independent set
  • Geometric intersection graph

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