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Faster deterministic sorting and searching in linear space

Conference ·
OSTI ID:457645

We present a significant improvement on linear space deterministic sorting and searching. On a unit-cost RAM with word size {omega}, an ordered set of n {omega}-bit keys (viewed as binary strings or integers) can be maintained in time per operation, including insert, delete, member search, and neighbor search. The cost for searching is worst-case while the cost for updates is amortized. As an application, n keys can be sorted in linear at O(n{radical}log n) worst-case cost. The best previous method for deterministic sorting and searching in linear space has been the fusion trees which supports updates and queries in O(log n/log log n) amortized time and sorting in O(n log n/log log n) worst-case time. We also make two minor observations on adapting our data structure to the input distribution and on the complexity of perfect hashing.

OSTI ID:
457645
Report Number(s):
CONF-961004--
Country of Publication:
United States
Language:
English

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