Near-Optimal Low-Congestion Shortcuts on Bounded Parameter Graphs

  • Bernhard HaeuplerEmail author
  • Taisuke Izumi
  • Goran ZuzicEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9888)


We show that many distributed network optimization problems can be solved much more efficiently in structured and topologically simple networks.

It is known that solving essentially any global network optimization problem in a general network requires \(\varOmega (\sqrt{n})\) rounds in the CONGEST model, even if the network diameter is small, e.g., logarithmic. Many networks of interest, however, have more structure which allows for significantly more efficient algorithms. Recently Ghaffari, Haeupler, Izumi and Zuzic [SODA’16,PODC’16] introduced low-congestion shortcuts as a suitable abstraction to capture this phenomenon. In particular, they showed that graphs with diameter D embeddable in a genus-g surface have good shortcuts and that these shortcuts lead to \(\tilde{O}(g D)\)-round algorithms for MST, Min-Cut and other problems.

We generalize these results by showing that networks with pathwidth or treewidth k allow for good shortcuts leading to fast \(\tilde{O}(k D)\) distributed optimization algorithms. We also improve the dependence on genus g from \(\tilde{O}(gD)\) to \(\tilde{O}(\sqrt{g}D)\). Lastly, we prove lower bounds which show that the dependence on k and g in our shortcuts is optimal. Overall, this significantly refines and extends the understanding of how the complexity of distributed optimization problems depends on the network topology.


Distributed algorithm CONGEST model Treewidth Pathwidth Bounded-genus graph Minimum spanning tree Minimum cut 



We are thankful to the Center for Exploring the Limits of Computation (ELC) and the Japan Society for the Promotion of Science for funding a three-week collaborative research visit. We also thank Mohsen Ghaffari for discussions and contributions at the beginning of this project and the DISC reviewers of this paper for their helpful comments.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  1. 1.Carnegie Mellon UniversityPittsburghUSA
  2. 2.Nagoya Institute of TechnologyNagoyaJapan

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