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  1. Home > Articles & Issues >
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  3. On unary nodes in tr ...
Conference paper

On unary nodes in tries

Stephan Wagner (1) (2)
(1) Department of Mathematical Sciences [Matieland, Stellenbosch Uni.]
(2) Department of Mathematical Sciences [Stellenbosch University]
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Imported on
January 31, 2017
Published on
December 31, 2009
Last modified on
March 31, 2025
Volume
DMTCS Proceedings vol. AM, 21st International Meeting on Probabilistic, Combinatorial, and Asymptotic Methods in the Analysis of Algorithms (AofA'10)
Proceedings
DOI
10.46298/dmtcs.2776
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https://about.hal.science/hal-authorisation-v1
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On unary nodes in tries

Stephan Wagner (1) (2)
(1) Department of Mathematical Sciences [Matieland, Stellenbosch Uni.]
(2) Department of Mathematical Sciences [Stellenbosch University]
Abstract
The difference between ordinary tries and Patricia tries lies in the fact that all unary nodes are removed in the latter. Their average number is thus easily determined from earlier results on the size of tries/Patricia tries. In a well-known contention resolution algorithm, whose probabilistic model is essentially equivalent to tries, unary nodes correspond to repetitions, i.e., steps in the algorithm that do not resolve anything at all. In this paper, we take an individual's view on such repetitions: we consider the distribution of the number of repetitions a certain contender encounters in the course of the algorithm―-which is equivalent to the number of unary nodes on the path from the root to a random string in a trie. We encounter an example of a sequence of distributions that does not actually converge to a limit distribution, but rather oscillates around a (discrete) limit distribution.
Keywords
  • [INFO.INFO-DS]Computer Science [cs]/Data Structures and Algorithms [cs.DS]
  • [MATH.MATH-CO]Mathematics [math]/Combinatorics [math.CO]
  • [INFO.INFO-DM]Computer Science [cs]/Discrete Mathematics [cs.DM]
  • [INFO.INFO-CG]Computer Science [cs]/Computational Geometry [cs.CG]
  • tries
  • Patricia tries
  • contention trees
  • unary nodes
  • limit distribution
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