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Non-adaptive Data Structure Lower Bounds for Predecessor Search Brody, Joshua
Description
In this work, we continue the examination of the role non-adaptivity plays in maintaining dynamic data structures, initiated by Brody and Larsen [BL15]}. We consider non-adaptive data structures for predecessor search in the w-bit cell probe model. Predecessor search is one of the most well-studied data structure problems. For this problem, using non-adaptivity comes at a steep price. We provide exponential cell probe complexity separations between (i) adaptive and non-adaptive data structures and (ii) non-adaptive and memoryless data structures for predecessor search.
A classic adaptive data structure of van Emde Boas solves dynamic predecessor search in $O(\log \log m)$ probes. For dynamic data structures which make non-adaptive updates, we show the cell probe complexity is $O(min{ (log m)/(log(w/log m)$, $(n log m)/w) })$. We also give a nearly-matching $\Omega( min {(log m)/(log w)$, $(nlog m)/(w log w) })$ lower bound. We also give an $\Omega(m)$ lower bound for memoryless data structures.
Our lower bound technique is tailored to non-adaptive (as opposed to memoryless) updates and might be of independent interest.
Joint work with Joe Boninger and Owen Kephart.
Item Metadata
| Title |
Non-adaptive Data Structure Lower Bounds for Predecessor Search
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| Creator | |
| Publisher |
Banff International Research Station for Mathematical Innovation and Discovery
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| Date Issued |
2017-03-21T11:21
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| Description |
In this work, we continue the examination of the role non-adaptivity plays in maintaining dynamic data structures, initiated by Brody and Larsen [BL15]}. We consider non-adaptive data structures for predecessor search in the w-bit cell probe model. Predecessor search is one of the most well-studied data structure problems. For this problem, using non-adaptivity comes at a steep price. We provide exponential cell probe complexity separations between (i) adaptive and non-adaptive data structures and (ii) non-adaptive and memoryless data structures for predecessor search.
A classic adaptive data structure of van Emde Boas solves dynamic predecessor search in $O(\log \log m)$ probes. For dynamic data structures which make non-adaptive updates, we show the cell probe complexity is $O(min{ (log m)/(log(w/log m)$, $(n log m)/w) })$. We also give a nearly-matching $\Omega( min {(log m)/(log w)$, $(nlog m)/(w log w) })$ lower bound. We also give an $\Omega(m)$ lower bound for memoryless data structures.
Our lower bound technique is tailored to non-adaptive (as opposed to memoryless) updates and might be of independent interest.
Joint work with Joe Boninger and Owen Kephart.
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| Extent |
24 minutes
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| Subject | |
| Type | |
| File Format |
video/mp4
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| Language |
eng
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| Notes |
Author affiliation: Swarthmore College
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| Series | |
| Date Available |
2017-09-17
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| Provider |
Vancouver : University of British Columbia Library
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| Rights |
Attribution-NonCommercial-NoDerivatives 4.0 International
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| DOI |
10.14288/1.0355679
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| URI | |
| Affiliation | |
| Peer Review Status |
Unreviewed
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| Scholarly Level |
Faculty
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| Rights URI | |
| Aggregated Source Repository |
DSpace
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Rights
Attribution-NonCommercial-NoDerivatives 4.0 International