竞争性在线搜索树对树

IF 0.9 3区 计算机科学 Q3 COMPUTER SCIENCE, THEORY & METHODS
Prosenjit Bose, Jean Cardinal, John Iacono, Grigorios Koumoutsos, Stefan Langerman
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引用次数: 0

摘要

我们考虑自适应数据结构的设计来搜索树结构空间的元素。我们使用基于旋转的在线二叉搜索树模型的自然泛化,其中底层搜索空间是树的顶点集。该模型基于分解图的简单结构,以前有几个名称,包括消除树、顶点排名和管道。当底层树是一条路径时,该模型与经典的二叉搜索树模型完全等效。在这个模型中,我们描述了一个在线O(log log n)竞争的搜索树数据结构,其中n是顶点的数量。这符合最著名的二叉搜索树的竞争比。我们的方法受到Tango树的启发,Tango树是一种在线二叉搜索树算法,但需要一些新的概念,包括我们称之为斯坦纳闭搜索树的概念,这可能是独立的兴趣。此外,我们的技术基于两层分解的新使用,首先从搜索空间到一组斯坦纳闭树,然后从这些树到路径。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Competitive Online Search Trees on Trees

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.

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来源期刊
ACM Transactions on Algorithms
ACM Transactions on Algorithms COMPUTER SCIENCE, THEORY & METHODS-MATHEMATICS, APPLIED
CiteScore
3.30
自引率
0.00%
发文量
50
审稿时长
6-12 weeks
期刊介绍: ACM Transactions on Algorithms welcomes submissions of original research of the highest quality dealing with algorithms that are inherently discrete and finite, and having mathematical content in a natural way, either in the objective or in the analysis. Most welcome are new algorithms and data structures, new and improved analyses, and complexity results. Specific areas of computation covered by the journal include combinatorial searches and objects; counting; discrete optimization and approximation; randomization and quantum computation; parallel and distributed computation; algorithms for graphs, geometry, arithmetic, number theory, strings; on-line analysis; cryptography; coding; data compression; learning algorithms; methods of algorithmic analysis; discrete algorithms for application areas such as biology, economics, game theory, communication, computer systems and architecture, hardware design, scientific computing
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