An integer program for Open Locating Dominating sets and its results on the hexagon-triangle infinite grid and other graphs

D. B. Sweigart, J. Presnell, R. Kincaid
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引用次数: 8

Abstract

This paper presents an integer linear program (ILP) for the identification of Open Locating Dominating Sets (OLD) of minimum cardinality and presents several results of the ILP on various graphs. The OLD is similar to an identifying code, but for an open neighborhood instead of closed. The OLD was introduced by Peter Slater and Suk J. Seo in 2010 as a method by which one could identify the location of an event at a node where a node in the set can detect events at adjacent nodes, but cannot detect an event at itself. This is perhaps more clear as a series of factories such that those with intrusion detection devices form an identifying code, but an intruder will disable the system at the factory into which she breaks, if so equipped. There are also applications in other areas such as router networks. This paper continues work by Alison Oldham at the College of William and Mary on the development and implementation of an ILP to identify such OLDs on finite graphs. We demonstrate and compare the results on 100 node randomly generated graphs of various constructions; Erdös-Renyi, Geometric and Scale-Free. We find that most graphs have a density near 1/3. We also explore the use of the ILP to generate OLDs for infinite grids, looking specifically at the hexagonal-triangular grid where we discover a new upper bound of 5/12 on the minimum density OLD for this grid. Finally, we extend this ILP to identify locating dominating sets that simultaneously satisfy open and closed neighborhood criteria, or Closed-Open Locating Dominating sets (COLD).
一个开放定位控制集的整数程序及其在六边形-三角形无限网格和其他图上的结果
本文给出了最小基数开定位支配集识别的整数线性规划,并给出了该规划在不同图上的几个结果。OLD类似于识别码,但适用于开放的社区而不是封闭的社区。OLD是由Peter Slater和Suk J. Seo在2010年引入的一种方法,通过该方法可以识别节点上事件的位置,其中集合中的节点可以检测相邻节点上的事件,但不能检测自身的事件。这一点也许更清楚,因为在一系列工厂中,那些有入侵检测设备的工厂形成了一个识别代码,但入侵者将使她闯入的工厂的系统失效,如果配备了这样的设备。在路由器网络等其他领域也有应用。本文继续了威廉玛丽学院的Alison Oldham的工作,研究了在有限图上识别此类old的ILP的开发和实现。我们在100个节点随机生成的各种结构的图上演示并比较了结果;Erdös-Renyi,几何和无比例。我们发现大多数图的密度接近1/3。我们还探索了使用ILP来生成无限网格的OLD,特别是在六边形三角形网格中,我们发现了该网格最小密度OLD的新上界为5/12。最后,我们将此ILP扩展到同时满足开邻域和闭邻域标准的定位控制集,即闭开定位控制集(COLD)。
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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