LCL Problems on Grids

S. Brandt, J. Hirvonen, Janne H. Korhonen, Tuomo Lempiäinen, P. Östergård, Christopher Purcell, J. Rybicki, J. Suomela, P. Uznański
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引用次数: 48

Abstract

LCLs or locally checkable labelling problems (e.g. maximal independent set, maximal matching, and vertex colouring) in the LOCAL model of computation are very well-understood in cycles (toroidal 1-dimensional grids): every problem has a complexity of O(1), Θ(log* n), or Θ(n), and the design of optimal algorithms can be fully automated. This work develops the complexity theory of LCL problems for toroidal 2-dimensional grids. The complexity classes are the same as in the 1-dimensional case: O(1), Θ(log* n), and Θ(n). However, given an LCL problem it is undecidable whether its complexity is Θ(log* n) or Θ(n) in 2-dimensional grids. Nevertheless, if we correctly guess that the complexity of a problem is Θ(log* n), we can completely automate the design of optimal algorithms. For any problem we can find an algorithm that is of a normal form A' o Sk, where A' is a finite function, Sk is an algorithm for finding a maximal independent set in kth power of the grid, and k is a constant. Finally, partially with the help of automated design tools, we classify the complexity of several concrete LCL problems related to colourings and orientations.
网格上的LCL问题
局部计算模型中的lcl或局部可检查标记问题(例如最大独立集,最大匹配和顶点着色)在循环(环形一维网格)中非常容易理解:每个问题的复杂性为O(1), Θ(log* n)或Θ(n),并且优化算法的设计可以完全自动化。本文发展了环面二维网格LCL问题的复杂性理论。复杂度类与一维情况下相同:O(1)、Θ(log* n)和Θ(n)。然而,给定一个LCL问题,在二维网格中它的复杂度是Θ(log* n)还是Θ(n)是无法确定的。然而,如果我们正确地猜出问题的复杂性是Θ(log* n),我们就可以完全自动化最优算法的设计。对于任何问题,我们都可以找到一种正规形式为a ' o Sk的算法,其中a '是一个有限函数,Sk是在网格的k次幂中寻找最大独立集的算法,k是一个常数。最后,在自动化设计工具的帮助下,我们对与颜色和方向相关的几个具体LCL问题的复杂性进行了分类。
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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