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Deterministic Sensitivity Oracles for Diameter, Eccentricities and All Pairs Distances

Authors Davide Bilò , Keerti Choudhary , Sarel Cohen , Tobias Friedrich , Martin Schirneck

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Davide Bilò
  • Department of Information Engineering, Computer Science and Mathematics, University of L'Aquila, Italy
Keerti Choudhary
  • Department of Computer Science and Engineering, Indian Institute of Technology Delhi, India
Sarel Cohen
  • School of Computer Science, The Academic College of Tel Aviv-Yaffo, Israel
Tobias Friedrich
  • Hasso Plattner Institute, University of Potsdam, Germany
Martin Schirneck
  • Hasso Plattner Institute, University of Potsdam, Germany

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Davide Bilò, Keerti Choudhary, Sarel Cohen, Tobias Friedrich, and Martin Schirneck. Deterministic Sensitivity Oracles for Diameter, Eccentricities and All Pairs Distances. In 49th International Colloquium on Automata, Languages, and Programming (ICALP 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 229, pp. 22:1-22:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)
https://doi.org/10.4230/LIPIcs.ICALP.2022.22

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.

Subject Classification

ACM Subject Classification
  • Theory of computation → Data structures design and analysis
  • Theory of computation → Pseudorandomness and derandomization
  • Mathematics of computing → Graph algorithms
Keywords
  • derandomization
  • diameter
  • eccentricity
  • fault-tolerant data structure
  • sensitivity oracle
  • space lower bound

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