Time complexity of distributed topological self-stabilization: The case of graph linearization

Dominik Gall, Riko Jacob, Andrea Richa, Christian Scheideler, Stefan Schmid, Hanjo Täubig

Research output: Chapter in Book/Report/Conference proceedingConference contribution

17 Scopus citations

Abstract

Topological self-stabilization is an important concept to build robust open distributed systems (such as peer-to-peer systems) where nodes can organize themselves into meaningful network topologies. The goal is to devise distributed algorithms that converge quickly to such a desirable topology, independently of the initial network state. This paper proposes a new model to study the parallel convergence time. Our model sheds light on the achievable parallelism by avoiding bottlenecks of existing models that can yield a distorted picture. As a case study, we consider local graph linearization-i.e., how to build a sorted list of the nodes of a connected graph in a distributed and self-stabilizing manner. We propose two variants of a simple algorithm, and provide an extensive formal analysis of their worst-case and best-case parallel time complexities, as well as their performance under a greedy selection of the actions to be executed.

Original languageEnglish (US)
Title of host publicationLATIN 2010
Subtitle of host publicationTheoretical Informatics - 9th Latin American Symposium, Proceedings
Pages294-305
Number of pages12
DOIs
StatePublished - 2010
Event9th Latin American Theoretical Informatics Symposium, LATIN 2010 - Oaxaca, Mexico
Duration: Apr 19 2010Apr 23 2010

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6034 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other9th Latin American Theoretical Informatics Symposium, LATIN 2010
CountryMexico
CityOaxaca
Period4/19/104/23/10

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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