Deterministic Sensitivity Oracles for Diameter, Eccentricities and All Pairs Distances

Davide Bilò; Keerti Choudhary; Sarel Cohen; Tobias Friedrich; Martin Schirneck

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arXiv · 2204.10679

Deterministic Sensitivity Oracles for Diameter, Eccentricities and All Pairs Distances

Davide Bilò·Keerti Choudhary·Sarel Cohen·Tobias Friedrich·Martin Schirneck

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Abstract

We construct data structures for extremal and pairwise distances in directed graphs in the presence of transient edge failures. Henzinger et al. [ITCS 2017] initiated the study of fault-tolerant (sensitivity) oracles for the diameter and vertex eccentricities. We extend this with a special focus on space efficiency. We present several new data structures, among them the first fault-tolerant eccentricity oracle for dual failures in subcubic space. We further prove lower bounds that show limits to approximation vs. space and diameter vs. space trade-offs for fault-tolerant oracles. They highlight key differences between data structures for undirected and directed graphs. Initially, our oracles are randomized leaning on a sampling technique frequently used in sensitivity analysis. Building on the work of Alon, Chechik, and Cohen [ICALP 2019] as well as Karthik and Parter [SODA 2021], we develop a hierarchical framework to derandomize fault-tolerant data structures. We first apply it to our own diameter and eccentricity oracles and then show its versatility by derandomizing algorithms from the literature: the distance sensitivity oracle of Ren [JCSS 2022] and the Single-Source Replacement Path algorithm of Chechik and Magen [ICALP 2020]. This way, we obtain the first deterministic distance sensitivity oracle with subcubic preprocessing time.

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Davide Bilò, Keerti Choudhary, Sarel Cohen, Tobias Friedrich, Martin Schirneck. 2022-04-22. Deterministic Sensitivity Oracles for Diameter, Eccentricities and All Pairs Distances. https://arxiv.org/abs/2204.10679

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