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dc.contributor.authorDemaine, Erik D
dc.contributor.authorIacono, John
dc.contributor.authorKoumoutsos, Grigorios
dc.contributor.authorLangerman, Stefan
dc.date.accessioned2021-02-24T19:58:09Z
dc.date.available2021-02-24T19:58:09Z
dc.date.submitted2019-03
dc.identifier.issn0302-9743
dc.identifier.urihttps://hdl.handle.net/1721.1/129995
dc.descriptionPart of the Lecture Notes in Computer Science book series (LNCS, volume 11532)
dc.description.abstractWe revisit self-adjusting external memory tree data structures, which combine the optimal (and practical) worst-case I/O performances of B-trees, while adapting to the online distribution of queries. Our approach is analogous to undergoing efforts in the BST model, where Tango Trees (Demaine et al. 2007) were shown to be O(loglogN) -competitive with the runtime of the best offline binary search tree on every sequence of searches. Here we formalize the B-Tree model as a natural generalization of the BST model. We prove lower bounds for the B-Tree model, and introduce a B-Tree model data structure, the Belga B-tree, that executes any sequence of searches within a O(loglogN) factor of the best offline B-tree model algorithm, provided B= log[superscript O(1)]N. We also show how to transform any static BST into a static B-tree which is faster by a Θ(log B) factor; the transformation is randomized and we show that randomization is necessary to obtain any significant speedup.en_US
dc.description.sponsorshipBelgian National Foundation for Scientific Research ( Grant MISU F 6001 1)en_US
dc.description.sponsorshipNational Science Foundation (U.S.) (Grant CCF-1533564)en_US
dc.language.isoen
dc.publisherSpringer International Publishingen_US
dc.relation.isversionof10.1007/978-3-030-19955-5_9en_US
dc.rightsCreative Commons Attribution-Noncommercial-Share Alikeen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/en_US
dc.sourcearXiven_US
dc.titleBelga B-Treesen_US
dc.typeArticleen_US
dc.identifier.citationDemaine, Erik D. et al. “Belga B-Trees.” 14th International Computer Science Symposium, Lecture Notes in Computer Science, 11532, Springer, 2019, 93-105. © 2019 The Author(s)en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Scienceen_US
dc.contributor.departmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratoryen_US
dc.relation.journalLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)en_US
dc.eprint.versionAuthor's final manuscripten_US
dc.type.urihttp://purl.org/eprint/type/ConferencePaperen_US
eprint.statushttp://purl.org/eprint/status/NonPeerRevieweden_US
dc.date.updated2020-12-07T19:38:18Z
dspace.orderedauthorsDemaine, ED; Iacono, J; Koumoutsos, G; Langerman, Sen_US
dspace.date.submission2020-12-07T19:38:22Z
mit.journal.volume11532en_US
mit.licenseOPEN_ACCESS_POLICY


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