Strongly Connected Spanning Subgraph for Almost Symmetric Networks

A. Karim Abu-Affash, Paz Carmi, Anat Parush Tzur

Research output: Contribution to journalArticlepeer-review

Abstract

In the strongly connected spanning subgraph (SCSS) problem, the goal is to find a minimum weight spanning subgraph of a strongly connected directed graph that maintains the strong connectivity. In this paper, we consider the SCSS problem for two families of geometric directed graphs; t-spanners and symmetric disk graphs. Given a constant t ≥ 1, a directed graph G is a t-spanner of a set of points V if, for every two points u and v in V, there exists a directed path from u to v in G of length at most t|uv|, where |uv| is the Euclidean distance between u and v. Given a set V of points in the plane such that each point u V has a radius ru, the symmetric disk graph of V is a directed graph G = (V,E), such that E = {(u,v): |uv|≤ ru and |uv|≤ rv}. Thus, if there exists a directed edge (u,v), then (v,u) exists as well. We present 3\4(t + 1) and 3\2 approximation algorithms for the SCSS problem for t-spanners and for symmetric disk graphs, respectively. Actually, our approach achieves a 34(t + 1)-approximation algorithm for all directed graphs satisfying the property that, for every two nodes u and v, the ratio between the shortest paths, from u to v and from v to u in the graph, is at most t.

Original languageEnglish
Pages (from-to)207-219
Number of pages13
JournalInternational Journal of Computational Geometry and Applications
Volume27
Issue number3
DOIs
StatePublished - 1 Sep 2017

Keywords

  • Computational geometry
  • approximation algorithms
  • strongly connected subgraphs
  • symmetric disk graphs
  • t-spanners

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Geometry and Topology
  • Computational Theory and Mathematics
  • Computational Mathematics
  • Applied Mathematics

Fingerprint

Dive into the research topics of 'Strongly Connected Spanning Subgraph for Almost Symmetric Networks'. Together they form a unique fingerprint.

Cite this