BibTeX Export for Optimal Space Lower Bound for Deterministic Self-Stabilizing Leader Election Algorithms

Copy to Clipboard Download

@InProceedings{blin_et_al:LIPIcs.OPODIS.2021.24,
  author =	{Blin, L\'{e}lia and Feuilloley, Laurent and Le Bouder, Gabriel},
  title =	{{Optimal Space Lower Bound for Deterministic Self-Stabilizing Leader Election Algorithms}},
  booktitle =	{25th International Conference on Principles of Distributed Systems (OPODIS 2021)},
  pages =	{24:1--24:12},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-219-8},
  ISSN =	{1868-8969},
  year =	{2022},
  volume =	{217},
  editor =	{Bramas, Quentin and Gramoli, Vincent and Milani, Alessia},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.OPODIS.2021.24},
  URN =		{urn:nbn:de:0030-drops-157997},
  doi =		{10.4230/LIPIcs.OPODIS.2021.24},
  annote =	{Keywords: Space lower bound, memory tight bound, self-stabilization, leader election, anonymous, identifiers, state model, ring topology}
}

The metadata provided by Dagstuhl Publishing on its webpages, as well as their export formats (such as XML or BibTeX) available at our website, is released under the CC0 1.0 Public Domain Dedication license. That is, you are free to copy, distribute, use, modify, transform, build upon, and produce derived works from our data, even for commercial purposes, all without asking permission. Of course, we are always happy if you provide a link to us as the source of the data.

Read the full CC0 1.0 legal code for the exact terms that apply: https://creativecommons.org/publicdomain/zero/1.0/legalcode

Questions / Remarks / Feedback
X

Feedback for Dagstuhl Publishing


Thanks for your feedback!

Feedback submitted

Could not send message

Please try again later or send an E-mail