Near-optimal distributed maximum flow

Mohsen Ghaffari, Andreas Karrenbauer, Fabian Kuhn, Christoph Lenzen, Boaz Patt-Shamir

Research output: Contribution to journalArticlepeer-review

Abstract

We present a near-optimal distributed algorithm for (1 + o(1))-approximation of single-commodity maximum flow in undirected weighted networks that runs in (D + √n) · n o (1) communication rounds in the CONGEST model. Here, n and D denote the number of nodes and the network diameter, respectively. This is the first improvement over the trivial bound of O(n 2 ), and it nearly matches the Ω( ~ D + √n)-round complexity lower bound. The development of the algorithm entails two subresults of independent interest: (i) A (D + √n) · n o (1) -round distributed construction of a spanning tree of average stretch n o (1) . (ii) A (D + √n) · n o (1) -round distributed construction of an n o (1) -congestion approximator consisting of the cuts induced by O(log n) virtual trees. The distributed representation of the cut approximator allows for evaluation in (D + √n) · n o (1) rounds. All our algorithms make use of randomization and succeed with high probability.

Original languageEnglish
Pages (from-to)2078-2117
Number of pages40
JournalSIAM Journal on Computing
Volume47
Issue number6
DOIs
StatePublished - 2018

Keywords

  • Approximation algorithm
  • CONGEST model
  • Congestion approximator
  • Gradient descent

All Science Journal Classification (ASJC) codes

  • General Computer Science
  • General Mathematics

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