Connectivity Labeling and Routing with Multiple Vertex Failures
Abstract
We present succinct labeling schemes for answering connectivity queries in graphs subject to a specified number of vertex failures. An $f$-vertex/edge fault tolerant ($f$-V/EFT) connectivity labeling is a scheme that produces succinct labels for the vertices (and possibly to the edges) of an $n$-vertex graph $G$, such that given only the labels of two vertices $s,t$ and of at most $f$ faulty vertices/edges $F$, one can infer if $s$ and $t$ are connected in $G-F$. The primary complexity measure is the maximum label length (in bits). The $f$-EFT setting is relatively well understood: [Dory and Parter, PODC 2021] gave a randomized scheme with succinct labels of $O(\log^3 n)$ bits, which was subsequently derandomized by [Izumi et al., PODC 2023] with $\tilde{O}(f^2)$-bit labels. As both noted, handling vertex faults is more challenging. The known bounds for the $f$-VFT setting are far away: [Parter and Petruschka, DISC 2022] gave $\tilde{O}(n^{1-1/2^{\Theta(f)}})$-bit labels, which is linear in $n$ already for $f =\Omega(\log\log n)$. In this work we present an efficient $f$-VFT connectivity labeling scheme using $poly(f, \log n)$ bits. Specifically, we present a randomized scheme with $O(f^3 \log^5 n)$-bit labels, and a derandomized version with $O(f^7 \log^{13} n)$-bit labels, compared to an $\Omega(f)$-bit lower bound on the required label length. Our schemes are based on a new low-degree graph decomposition that improves on [Duan and Pettie, SODA 2017], and facilitates its distributed representation into labels. Finally, we show that our labels naturally yield routing schemes avoiding a given set of at most $f$ vertex failures with table and header sizes of only $poly(f,\log n)$ bits. This improves significantly over the linear size bounds implied by the EFT routing scheme of Dory and Parter.
- Publication:
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arXiv e-prints
- Pub Date:
- July 2023
- DOI:
- 10.48550/arXiv.2307.06276
- arXiv:
- arXiv:2307.06276
- Bibcode:
- 2023arXiv230706276P
- Keywords:
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- Computer Science - Data Structures and Algorithms;
- Computer Science - Discrete Mathematics