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Batched Predecessor and Sorting with Size-Priced Information in External Memory

  • City University of New York
  • International University of Sarajevo
  • Alphabet Inc.
  • Aristotle University of Thessaloniki

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

The fundamental problems of sorting and searching, traditionally studied in the unit-cost comparison model, have been generalized to include priced information, where different pairs of items have different comparison costs. These costs can be arbitrary (Charikar et al. STOC 2000), structured (Gupta et al. FOCS 2001), or stochastic (Angelov et al. LATIN 2008). Motivated by the database setting where the comparison cost depends on the sizes of the records, we consider the problems of sorting and batched predecessor where two non-uniform sets of items A and B are given as input. In the RAM model, pairwise comparisons (A-A, A-B and B-B) have respective comparison costs a, b and c. We give upper and lower bounds for the case a≤ b≤ c, which serves as a warmup for the generalization to the external-memory model. In the Disk-Access Model (DAM), where transferring elements between disk and RAM is the main bottleneck, we consider the scenario where elements in B are larger than elements in A. All items are required in their entirety for comparisons in RAM. A key observation is that the complexity of sorting depends on the interleaving of the small and large items in the final sorted order, and with a high degree of interleaving, the lower bound is dominated by an associated batched predecessor problem. We give output-sensitive bounds on the batched predecessor and sorting; our bounds are tight in most cases. Our lower bounds require novel generalizations of lower bound techniques in external memory to accommodate non-uniform keys.

Original languageEnglish
Title of host publicationLATIN 2020
Subtitle of host publicationTheoretical Informatics - 14th Latin American Symposium 2021, Proceedings
EditorsYoshiharu Kohayakawa, Flávio Keidi Miyazawa
PublisherSpringer Science and Business Media Deutschland GmbH
Pages155-167
Number of pages13
ISBN (Print)9783030617912
DOIs
StatePublished - 2020
Event14th Latin American Symposium on Theoretical Informatics, LATIN 2020 - Sao Paulo, Brazil
Duration: Jan 5 2021Jan 8 2021

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12118 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference14th Latin American Symposium on Theoretical Informatics, LATIN 2020
Country/TerritoryBrazil
CitySao Paulo
Period01/5/2101/8/21

Keywords

  • Batched predecessor
  • External memory
  • Output-sensitive algorithms
  • Priced information
  • Sorting

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