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        <identifier>oai:drops-oai.dagstuhl.de:17223</identifier>
        <datestamp>2024-03-06T10:59:16Z</datestamp>
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          <dc:title>Õptimal Dual Vertex Failure Connectivity Labels</dc:title>
          <dc:creator>Parter, Merav</dc:creator>
          <dc:creator>Petruschka, Asaf</dc:creator>
          <dc:subject>Fault-Tolerance</dc:subject>
          <dc:subject>Heavy-Light Decomposition</dc:subject>
          <dc:subject>Labeling Schemes</dc:subject>
          <dc:description>In this paper we present succinct labeling schemes for supporting connectivity queries under vertex faults. For a given n-vertex graph G, an f-VFT (resp., EFT) connectivity labeling scheme is a distributed data structure that assigns each of the graph edges and vertices a short label, such that given the labels of a vertex pair u and v, and the labels of at most f failing vertices (resp., edges) F, one can determine if u and v are connected in G ⧵ F. The primary complexity measure is the length of the individual labels. Since their introduction by [Courcelle, Twigg, STACS '07], FT labeling schemes have been devised only for a limited collection of graph families. A recent work [Dory and Parter, PODC 2021] provided EFT labeling schemes for general graphs under edge failures, leaving the vertex failure case fairly open. &#13;
We provide the first sublinear f-VFT labeling schemes for f ≥ 2 for any n-vertex graph. Our key result is 2-VFT connectivity labels with O(log³ n) bits. Our constructions are based on analyzing the structure of dual failure replacement paths on top of the well-known heavy-light tree decomposition technique of [Sleator and Tarjan, STOC 1981]. We also provide f-VFT labels with sub-linear length (in |V|) for any f = o(log log n), that are based on a reduction to the existing EFT labels.</dc:description>
          <dc:publisher>Schloss Dagstuhl – Leibniz-Zentrum für Informatik</dc:publisher>
          <dc:contributor>Merav Parter and Asaf Petruschka</dc:contributor>
          <dc:date>2022</dc:date>
          <dc:relation>Is Part Of LIPIcs, Volume 246, 36th International Symposium on Distributed Computing (DISC 2022)</dc:relation>
          <dc:type>InProceedings</dc:type>
          <dc:type>Text</dc:type>
          <dc:type>doc-type:ResearchArticle</dc:type>
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          <dc:identifier>doi:10.4230/LIPIcs.DISC.2022.32</dc:identifier>
          <dc:identifier>urn:nbn:de:0030-drops-172239</dc:identifier>
          <dc:identifier>https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.DISC.2022.32</dc:identifier>
          <dc:language>eng</dc:language>
          <dc:rights>https://creativecommons.org/licenses/by/4.0/legalcode</dc:rights>
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