Affiliation:
1. Carleton University, Canada
2. Université libre de Bruxelles (ULB), Belgium
Abstract
We consider the design of adaptive data structures for searching elements of a tree-structured space. We use a natural generalization of the rotation-based online binary search tree model in which the underlying search space is the set of vertices of a tree. This model is based on a simple structure for decomposing graphs, previously known under several names including elimination trees, vertex rankings, and tubings. The model is equivalent to the classical binary search tree model exactly when the underlying tree is a path. We describe an online
O
(log log
n
)-competitive search tree data structure in this model, where
n
is the number of vertices. This matches the best-known competitive ratio of binary search trees. Our method is inspired by Tango trees, an online binary search tree algorithm, but critically needs several new notions including one that we call Steiner-closed search trees, which may be of independent interest. Moreover, our technique is based on a novel use of two levels of decomposition, first from search space to a set of Steiner-closed trees and, second, from these trees into paths.
Funder
European Union’s Horizon 2020
NSERC
Fonds de la Recherche Scientifique-FNRS
NSF AitF
Publisher
Association for Computing Machinery (ACM)
Subject
Mathematics (miscellaneous)
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