Dynamic Distribution-Sensitive Point Location

Siu-Wing Cheng, Man-Kit Lau
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Abstract

We propose a dynamic data structure for the distribution-sensitive point location problem in the plane. Suppose that there is a fixed query distribution within a convex subdivision S, and we are given an oracle that can return in O(1) time the probability of a query point falling into a polygonal region of constant complexity. We can maintain S such that each query is answered in Oopt(S)) expected time, where opt (S) is the expected time of the best linear decision tree for answering point location queries in S. The space and construction time are O(nlog2n), where n is the number of vertices of S. An update of S as a mixed sequence of k edge insertions and deletions takes O(klog4 n) amortized time. As a corollary, the randomized incremental construction of the Voronoi diagram of n sites can be performed in O(nlog4 n) expected time so that, during the incremental construction, a nearest neighbor query at any time can be answered optimally with respect to the intermediate Voronoi diagram at that time.
动态分布敏感点定位
针对平面上的分布敏感点定位问题,提出了一种动态数据结构。假设在一个凸细分S内存在一个固定的查询分布,并且给定一个可以在O(1)时间内返回查询点落入一个恒定复杂度的多边形区域的概率的oracle。我们可以维持S,使得每个查询在Oopt(S))期望时间内得到回答,其中opt(S)是回答S中点位置查询的最佳线性决策树的期望时间。空间和构建时间为O(nlog2n),其中n为S的顶点数。将S更新为k个边插入和删除的混合序列需要O(klog4n)平摊时间。作为推论,n个站点的Voronoi图的随机增量构建可以在O(nlog4n)期望时间内完成,因此在增量构建过程中,任何时候的最近邻查询都可以相对于当时的中间Voronoi图得到最优回答。
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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