Space-Efficient Algorithms for Reachability in Directed Geometric Graphs

Authors Sujoy Bhore , Rahul Jain

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Author Details

Sujoy Bhore
  • Indian Institute of Science Education and Research, Bhopal, India
Rahul Jain
  • Fernuniversität in Hagen, Germany

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Sujoy Bhore and Rahul Jain. Space-Efficient Algorithms for Reachability in Directed Geometric Graphs. In 32nd International Symposium on Algorithms and Computation (ISAAC 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 212, pp. 63:1-63:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)


The problem of graph Reachability is to decide whether there is a path from one vertex to another in a given graph. In this paper, we study the Reachability problem on three distinct graph families - intersection graphs of Jordan regions, unit contact disk graphs (penny graphs), and chordal graphs. For each of these graph families, we present space-efficient algorithms for the Reachability problem. For intersection graphs of Jordan regions, we show how to obtain a "good" vertex separator in a space-efficient manner and use it to solve the Reachability in polynomial time and O(m^{1/2} log n) space, where n is the number of Jordan regions, and m is the total number of crossings among the regions. We use a similar approach for chordal graphs and obtain a polynomial time and O(m^{1/2} log n) space algorithm, where n and m are the number of vertices and edges, respectively. However, for unit contact disk graphs (penny graphs), we use a more involved technique and obtain a better algorithm. We show that for every ε > 0, there exists a polynomial time algorithm that can solve Reachability in an n vertex directed penny graph, using O(n^{1/4+ε}) space. We note that the method used to solve penny graphs does not extend naturally to the class of geometric intersection graphs that include arbitrary size cliques.

Subject Classification

ACM Subject Classification
  • Theory of computation → Computational geometry
  • Reachablity
  • Geometric intersection graphs
  • Space-efficient algorithms


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