Brief Announcement: Minimizing Congestion in Hybrid Demand-Aware Network Topologies

Authors Wenkai Dai , Michael Dinitz , Klaus-Tycho Foerster , Stefan Schmid

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Author Details

Wenkai Dai
  • Faculty of Computer Science, Universität Wien, Austria
Michael Dinitz
  • Computer Science Department, Johns Hopkins University, Baltimore, MD, USA
Klaus-Tycho Foerster
  • Computer Science Department, Technische Universität Dortmund, Germany
Stefan Schmid
  • TU Berlin, Germany
  • Faculty of Computer Science, Universität Wien, Austria

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Wenkai Dai, Michael Dinitz, Klaus-Tycho Foerster, and Stefan Schmid. Brief Announcement: Minimizing Congestion in Hybrid Demand-Aware Network Topologies. In 36th International Symposium on Distributed Computing (DISC 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 246, pp. 42:1-42:3, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)


Emerging reconfigurable optical communication technologies enable demand-aware networks: networks whose static topology can be enhanced with demand-aware links optimized towards the traffic pattern the network serves. This paper studies the algorithmic problem of how to jointly optimize the topology and the routing in such demand-aware networks, to minimize congestion. We investigate this problem along two dimensions: (1) whether flows are splittable or unsplittable, and (2) whether routing on the hybrid topology is segregated or not, i.e., whether or not flows either have to use exclusively either the static network or the demand-aware connections. For splittable and segregated routing, we show that the problem is 2-approximable in general, but APX-hard even for uniform demands induced by a bipartite demand graph. For unsplittable and segregated routing, we show an upper bound of O(log m/ log log m) and a lower bound of Ω(log m/ log log m) for polynomial-time approximation algorithms, where m is the number of static links. Under splittable (resp., unsplittable) and non-segregated routing, even for demands of a single source (resp., destination), the problem cannot be approximated better than Ω(c_{max}/c_{min}) unless P=NP, where c_{max} (resp., c_{min}) denotes the maximum (resp., minimum) capacity. It is still NP-hard for uniform capacities, but can be solved efficiently for a single commodity and uniform capacities.

Subject Classification

ACM Subject Classification
  • Networks → Network architectures
  • Theory of computation → Design and analysis of algorithms
  • Congestion
  • Reconfigurable Networks
  • Algorithms
  • Complexity


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