具有次多项式最坏情况更新时间的动态最小生成森林

Danupon Nanongkai, Thatchaphol Saranurak, Christian Wulff-Nilsen
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引用次数: 112

摘要

我们提出了一种Las Vegas算法,用于动态维护n节点图的最小生成森林,并进行边缘插入和删除。我们的算法保证了高概率的O(n^{O(1)})}最坏情况下的更新时间。这大大改进了最近的两种Las Vegas算法,前者是Wulff-Nilsen \cite{Wulff-Nilsen16a},更新时间为O(n^{0.5-≥ ilm}),后者是Nanongkai和Saranurak \cite{NanongkaiS16},更新时间为O(n^{0.494})(后者仅适用于维护生成森林)。我们的结果是通过识别两种算法所依赖的共同框架,然后改进和结合两者的思想得到的。该框架中有两个主要的算法组件是新改进的,对于获得我们的结果至关重要。首先,我们将更新时间从\cite{Wulff-Nilsen16a}中的O(n^{0.5-≥ ilm})提高到O(n^{O(1)}),用于逐步去除正在进行边缘删除的扩展器中的所有低电导切口。其次,通过回顾Henzinger和King \cite{HenzingerK97b}以及Holm等人\cite{HolmLT01的收缩技术,我们展示了一种在很少(最多(1+o(1))n)条边的连通图中维护最小生成森林的新方法。这大大改进了先前基于frederickson二维拓扑树的方法\cite{Frederickson85},并说明了该旧技术的新应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Dynamic Minimum Spanning Forest with Subpolynomial Worst-Case Update Time
We present a Las Vegas algorithm for dynamically maintaining a minimum spanning forest of an n-node graph undergoing edge insertions and deletions. Our algorithm guarantees an O(n^{o(1)})} worst-case} update time with high probability. This significantly improves the two recent Las Vegas algorithms by Wulff-Nilsen \cite{Wulff-Nilsen16a} with update time O(n^{0.5-≥ilon}) for some constant ≥ilon 0 and, independently, by Nanongkai and Saranurak \cite{NanongkaiS16} with update time O(n^{0.494}) (the latter works only for maintaining a spanning forest).Our result is obtained by identifying the common framework that both two previous algorithms rely on, and then improve and combine the ideas from both works. There are two main algorithmic components of the framework that are newly improved and critical for obtaining our result. First, we improve the update time from O(n^{0.5-≥ilon}) in \cite{Wulff-Nilsen16a} to O(n^{o(1)}) for decrementally removing all low-conductance cuts in an expander undergoing edge deletions. Second, by revisiting the contraction technique by Henzinger and King \cite{HenzingerK97b} and Holm et al. \cite{HolmLT01, we show a new approach for maintaining a minimum spanning forest in connected graphs with very few (at most (1+o(1))n) edges. This significantly improves the previous approach in \cite{Wulff-Nilsen16a, NanongkaiS16} which is based on Fredericksons 2-dimensional topology tree \cite{Frederickson85} and illustrates a new application to this old technique.
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