Predecessor Queries in Constant Time?

Ontology type: schema:Chapter

Chapter Info

DATE

2005

AUTHORS ABSTRACT

In this paper we design a new static data structure for batched predecessor queries. In particular, our data structure supports \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$O(\sqrt{{\rm log}n})$\end{document} queries in O(1) time per query and requires \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$O(n^{\epsilon\sqrt{{\rm log}n}})$\end{document} space for any ε > 0. This is the first o(N) space and O(1) amortized time data structure for arbitrary \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$N = \Omega(n^{\epsilon\sqrt{{\rm log}n}})$\end{document} where N is the size of the universe. We also present a data structure that answers O(log log N) predecessor queries in O(1) time per query and requires \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$O(n^{\epsilon{\rm log log} {\it N}})$\end{document} space for any ε > 0. The method of solution relies on a certain way of searching for predecessors of all elements of the query in parallel.In a general case, our approach leads to a data structure that supports p(n) queries in \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$O(\sqrt{{\rm log} n}/p(n))$\end{document} time per query and requires O(n\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$^{p({\it n})}$\end{document}) space for any \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$p(n) =O(\sqrt{{\rm log}n})$\end{document}, and a data structure that supports p(N) queries in O(log log N/p(N)) time per query and requires O(n\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$^{p({\it N})}$\end{document}) space for any p(N)=O(log log N). More... »

PAGES

238-248

Book

TITLE

Algorithms – ESA 2005

ISBN

978-3-540-29118-3
978-3-540-31951-1

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/11561071_23

DOI

http://dx.doi.org/10.1007/11561071_23

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1021245417

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