An optimal construction method for generalized convex layers

Hans-Peter Lenhof, M. Smid
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引用次数: 3

Abstract

Let P be a set of n points in the Euclidean plane and let C be a convex figure. In 1985, Chazelle and Edelsbrunner presented an algorithm, which preprocesses P such that for any query point q, the points of P in the translate C+q can be retrieved efficiently. Assuming that constant time suffices for deciding the inclusion of a point in C, they provided a space and query time optimal solution. Their algorithm uses O(n) space. A query with output size k can be solved in O(log n+k) time. The preprocessing step of their algorithm, however, has time complexity O(n2). We show that the usage of a new construction method for layers reduces the preprocessing time to O(n log n). We thus provide the first space, query time and preprocessing time optimal solution for this class of point retrieval problems. Besides, we present two new dynamic data structures for these problems. The first dynamic data structure allows on-line insertions and deletions of points in O((log n)2) time. In this dynamic data structure, a query with output size k can be solved in O(log n+k(log n)2) time. The second dynamic data structure, which allows only semi-online updates, has O((log n)2) amortized update time and O(log n+k) query time.
广义凸层的最优构造方法
设P是欧几里得平面上n个点的集合,设C是一个凸图形。1985年,Chazelle和Edelsbrunner提出了一种算法,该算法对P进行预处理,使得对于任意查询点q,可以有效地检索到平移C+q中的P点。假设常数时间足以决定C中是否包含一个点,他们给出了空间和查询时间的最优解。他们的算法使用O(n)空间。输出大小为k的查询可以在O(log n+k)时间内解决。然而,其算法的预处理步骤的时间复杂度为O(n2)。我们证明了使用一种新的层构造方法将预处理时间减少到O(n log n),从而为这类点检索问题提供了第一空间、查询时间和预处理时间的最优解。此外,我们还针对这些问题提出了两种新的动态数据结构。第一个动态数据结构允许在O((log n)2)时间内在线插入和删除点。在这种动态数据结构中,输出大小为k的查询可以在O(log n+k(log n)2)时间内解决。第二种动态数据结构只允许半在线更新,它的平摊更新时间为O((log n)2),查询时间为O(log n+k)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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