A Nearly Time-Optimal Population Protocol for Self-Stabilizing Leader Election on Rings with Polylogarithmic States

[2305.08375] A Nearly Time-Optimal Population Protocol for Self-Stabilizing Leader Election on Rings with Polylogarithmic States Skip to main content Search Submit Donate Log in Search arXiv Press Enter to search · Advanced search Computer Science > Distributed, Parallel, and Cluster Computing arXiv:2305.08375 (cs) [Submitted on 15 May 2023 ( v1 ), last revised 16 Aug 2026 (this version, v2)] Title: A Nearly Time-Optimal Population Protocol for Self-Stabilizing Leader Election on Rings with Polylogarithmic States Authors: Daisuke Yokota , Yuichi Sudo , Fukuhito Ooshita , Toshimitsu Masuzawa View a PDF of the paper titled A Nearly Time-Optimal Population Protocol for Self-Stabilizing Leader Election on Rings with Polylogarithmic States, by Daisuke Yokota and 3 other authors View PDF HTML (experimental) Abstract: We propose a self-stabilizing leader election (SS-LE) protocol on ring networks in the population protocol model. Given an integer $\psi$ satisfying $\log n \le \psi \le \log n+O(1)$, where $n$ is the population size, the proposed protocol reaches a safe configuration within $O(n^2 \log n)$ steps with high probability from any initial configuration, and thereafter preserves the same unique leader forever. Since no protocol solves SS-LE in $o(n^2)$ steps with high probability, the convergence time is near-optimal, with only an $O(\log n)$ multiplicative gap. The proposed protocol uses only $\mathit{polylog}(n)$ states. Two state-of-the-art protocols are known for SS-LE on ring networks. The first protocol uses a polynomial number of states and solves SS-LE in $O(n^2)$ steps, whereas the second protocol requires super-exponential time but uses only a constant number of states. Our proposed protocol provides a useful middle ground between these two approaches. Subjects: Distributed, Parallel, and Cluster Computing (cs.DC) Cite as: arXiv:2305.08375 [cs.DC] (or arXiv:2305.08375v2 [cs.DC] for this version) https://doi.org/10.48550/arXiv.2305.08375 Focus to learn more arXiv-issued DOI via DataCite Submission history From: Yuichi Sudo [ view email ] [v1] Mon, 15 May 2023 06:21:47 UTC (115 KB) [v2] Sun, 16 Aug 2026 09:28:07 UTC (92 KB) Full-text links: Access Paper: View a PDF of the paper titled A Nearly Time-Optimal Population Protocol for Self-Stabilizing Leader Election on Rings with Polylogarithmic States, by Daisuke Yokota and 3 other authors View PDF HTML (experimental) TeX Source view license Current browse context: cs.DC < prev | next > new | recent | 2023-05 Change to browse by: cs References & Citations NASA ADS Google Scholar Semantic Scholar export BibTeX citation Loading... BibTeX formatted citation × loading... Data provided by: Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer ( What is the Explorer? ) Connected Papers Toggle Connected Papers ( What is Connected Papers? ) Litmaps Toggle Litmaps ( What is Litmaps? ) scite.ai Toggle scite Smart Citations ( What are Smart Citations? ) Code, Data, Media Code, Data and Media Associated with this Article alphaXiv Toggle alphaXiv ( What is alphaXiv? ) Links to Code Toggle CatalyzeX Code Finder for Papers ( What is CatalyzeX? ) DagsHub Toggle DagsHub ( What is DagsHub? ) GotitPub Toggle Gotit.pub ( What is GotitPub? ) Huggingface Toggle Hugging Face ( What is Huggingface? ) ScienceCast Toggle ScienceCast ( What is ScienceCast? ) Demos Demos Replicate Toggle Replicate ( What is Replicate? ) Spaces Toggle Hugging Face Spaces ( What is Spaces? ) Spaces Toggle TXYZ.AI ( What is TXYZ.AI? ) Related Papers Recommenders and Search Tools Link to Influence Flower Influence Flower ( What are Influence Flowers? ) Core recommender toggle CORE Recommender ( What is CORE? ) Author Venue Institution Topic About arXivLabs arXivLabs: experimental projects with community collaborators arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs . Which authors of this paper are endorsers? | Disable MathJax ( What is MathJax? ) We gratefully acknowledge support from our major funders , member institutions , , and all contributors. About · Help · Contact · Subscribe · Copyright · Privacy · Accessibility · Operational Status (opens in new tab) Major funding support from

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