Distributed Self-Adjusting Tree Networks

Bruna Peres, Otavio A.De O. Souza, Olga Goussevskaia, Chen Avin, Stefan Schmid

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

18 Scopus citations


We consider the problem of designing dynamic network topologies that self-adjust to the (possibly changing) traffic pattern they serve. Such demand-aware networks currently receive much attention, especially in the context of datacenters, due to emerging technologies supporting the fast reconfiguration of the physical topology. We present the first fully distributed, provably efficient self-adjusting network. Our network called DiSptayNet relies on algorithms that perform decentralized and concurrent topological adjustments to account for changes in the demand. We present a rigorous formal analysis of the correctness and performance of DiSptayNet, which can be seen as an interesting generalization of analyses known from sequential self-adjusting datastructures. We also report on results from extensive trace-driven simulations.

Original languageEnglish
Title of host publicationINFOCOM 2019 - IEEE Conference on Computer Communications
PublisherInstitute of Electrical and Electronics Engineers
Number of pages9
ISBN (Electronic)9781728105154
StatePublished - 1 Apr 2019
Event2019 IEEE Conference on Computer Communications, INFOCOM 2019 - Paris, France
Duration: 29 Apr 20192 May 2019

Publication series

NameProceedings - IEEE INFOCOM
ISSN (Print)0743-166X


Conference2019 IEEE Conference on Computer Communications, INFOCOM 2019

ASJC Scopus subject areas

  • General Computer Science
  • Electrical and Electronic Engineering


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