Disjoint Paths in Densely Embedded Graphs (Preprint)

Abstract

We consider the following maximum disjoint paths problem (MDPP). We are given a large network, and pairs of nodes that wish to communicate over paths through the network -- the goal is to simultaneously connect as many of these pairs as possible in such a way that no two communication paths share an edge in the network. This classical problem has been brought into focus recently in papers discussing applications to routing in high-speed networks, where the current lack of understanding of the MDPP is an obstacle to the design of practical heuristics. We consider the class of densely embedded, nearly-Eulerian graphs, which includes the two-dimensional mesh and many other planar and locally planar interconnection networks. We obtain a constant-factor approximation algorithm for the maximum disjoint paths problem for this class of graphs; this improves on an O(log n)-approximation for the special case of the two-dimensional mesh due to Aumann-Rabani and the authors. For networks that are not explicitly required to be "high-capacity," this is the first constant-factor approximation for the MDPP in any class of graphs other than trees. We also consider the MDPP in the on-line setting, relevant to applications in which connection requests arrive over time and must be processed immediately. Here we obtain an asymptotically optimal O(log )-competitive on-line algorithm for the same class of graphs; this improves on an O(log n log log n)-competitive algorithm for the special case of the mesh due to Awerbuch, Gawlick, Leighton, and Rabani.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Oct 01, 1995
Accession Number
ADA640222

Entities

People

  • Jon Kleinberg
  • Éva Tardos

Organizations

  • Massachusetts Institute of Technology

Tags

Communities of Interest

  • C4I

DTIC Thesaurus Topics

  • Algorithms
  • Analogs
  • Bandwidth
  • Boundaries
  • Computer Science
  • Congestion
  • Crossings
  • Diameters
  • Electronic Mail
  • Intervals
  • Iterations
  • Notation
  • Operations Research
  • Polynomials
  • Probability
  • Simulations
  • Two Dimensional

Fields of Study

  • Computer science

Readers

  • Computer Networking
  • Graph Algorithms and Convex Optimization.