We study geometric variations of the discriminating code problem. In the discrete version of the problem, a finite set of points P and a finite set of objects S are given in R-d. The objective is to choose a subset S*...
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We study geometric variations of the discriminating code problem. In the discrete version of the problem, a finite set of points P and a finite set of objects S are given in R-d. The objective is to choose a subset S*subset of S of minimum cardinality such that for each point pi E P, the subset Si*subset of S* covering pi satisfies Si*not equal 0, and each pair p(i), p(j) is an element of P, i not equal j, we have S-i* not equal S-j*. In the continuous version of the problem, the solution set S* can be chosen freely among a (potentially infinite) class of allowed geometric objects. In the 1-dimensional case (d = 1), the points in P are placed on a horizontal line L, and the objects in S are finite-length line segments aligned with L (called intervals). We show that the discrete version of this problem is NP-complete. This is somewhat surprising as the continuous version is known to be polynomial time solvable. This is also in contrast with most geometric covering problems, which are usually polynomial-time solvable in one dimension. Still for the 1-dimensional discrete version, we design a polynomial-time 2-approximation algorithm. We also design a PTAS for both discrete and continuous versions in one dimension, for the restriction where the intervals are all required to have the same length. We then study the 2-dimensional case (d = 2) for axis-parallel unit square objects. We show that both continuous and discrete versions are NP-complete, and design polynomial-time approximation algorithms that produce (16 center dot O PT +1)-approximate and (64 center dot O PT + 1)-approximate solutions respectively, using rounding of suitably defined integer linear programming problems. Finally, we apply our techniques to a related variant of the discrete problem, where instead of points and geometric objects we just have a set S of objects. The goal is to select a small subset S* of objects so that all objects of S are discriminated by their intersection with the objects of S*
The watching system, as a generalization of identifying code, has been defined by Auger in 2010. The identifying code has been used to wireless networks and it has been also applied to locate objects in the sensor net...
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The watching system, as a generalization of identifying code, has been defined by Auger in 2010. The identifying code has been used to wireless networks and it has been also applied to locate objects in the sensor networks. On the other hand, the graph product is employed in most of the mathematic branches such as network design to study the structure of network elements. In this paper, we give some upper bounds for the watching number of well-know product graphs. (C) 2020 Elsevier Inc. All rights reserved.
The problems of determining minimum identifying, locating-dominating, open locating-dominating or locating total-dominating codes in a graph G are variations of the classical minimum dominating set problem in G and ar...
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The problems of determining minimum identifying, locating-dominating, open locating-dominating or locating total-dominating codes in a graph G are variations of the classical minimum dominating set problem in G and are all known to be hard for general graphs. A typical line of attack is therefore to determine the cardinality of minimum such codes in special graphs. In this work we study the change of minimum such codes under three operations in graphs: adding a universal vertex, taking the generalized corona of a graph, and taking the square of a graph. We apply these operations to paths and cycles which allows us to provide minimum codes in most of the resulting graph classes.
We study a monitoring problem on the surface of the earth for significant environmental, social/political and extreme events using satellites as sensors. We assume that the surface of the earth is divided into a set o...
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ISBN:
(纸本)9781450360944
We study a monitoring problem on the surface of the earth for significant environmental, social/political and extreme events using satellites as sensors. We assume that the surface of the earth is divided into a set of regions, where a region may be a continent, a country, or a set of neighboring countries. We also assume that, the impact of a significant event spills into neighboring regions and there will be corresponding indicators of such events. Careful deployment of sensors, utilizing identifying codes, can ensure that even though the number of deployed sensors is fewer than the number of regions, it may be possible to uniquely identify the region where the event has taken place. We assume that an event is confined to a region. As Earth is almost a sphere, we use a soccer ball (a sphere) as a model. From the model, we construct a Soccer Ball Graph (SBG), and show that the SBG has at least 26 sets of identifying codes of cardinality ten, implying that there are at least 26 different ways to deploy ten satellites to monitor the Earth. Finally, we also show that the size of the minimum identifying code for the SBG is at least nine.
The problems of determining minimum identifying, locating-dominating, open locating-dominating or locating total-dominating codes in a graph G are variations of the classical minimum dominating set problem in G and ar...
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The problems of determining minimum identifying, locating-dominating, open locating-dominating or locating total-dominating codes in a graph G are variations of the classical minimum dominating set problem in G and are all known to be hard for general graphs. A typical line of attack is therefore to determine the cardinality of minimum such codes in special graphs. In this work we study the change of minimum such codes under three operations in graphs: adding a universal vertex, taking the generalized corona of a graph, and taking the square of a graph. We apply these operations to paths and cycles which allows us to provide minimum codes in most of the resulting graph classes.
Assume that a graph G$$ G $$ models a detection system for a facility with a possible "intruder," or a multiprocessor network with a possible malfunctioning processor. We consider the problem of placing dete...
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Assume that a graph G$$ G $$ models a detection system for a facility with a possible "intruder," or a multiprocessor network with a possible malfunctioning processor. We consider the problem of placing detectors at a subset of vertices in G$$ G $$ to determine the location of an intruder if there is any. Many types of detection systems have been defined for different sensor capabilities;in particular, we focus on identifying codes, where each detector can determine whether there is an intruder within its closed neighborhood. In this research we explore a fault-tolerant variant of identifying codes applicable to real-world systems. Specifically, error-detecting identifying codes permit a false-negative transmission from any single detector. We investigate minimum-sized error-detecting identifying codes in several classes of graphs, including cubic graphs and infinite grids, and show that the problem of determining said minimum size in arbitrary graphs is NP-complete.
A set S of vertices of a digraph D is called an open neighbourhood locating -dominating set if every vertex in D has an in -neighbour in S, and for every pair u, v of vertices of D, there is a vertex in S that is an i...
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A set S of vertices of a digraph D is called an open neighbourhood locating -dominating set if every vertex in D has an in -neighbour in S, and for every pair u, v of vertices of D, there is a vertex in S that is an in -neighbour of exactly one of u and v. The smallest size of an open neighbourhood locating -dominating set of a digraph D is denoted by gamma OL(D). We study the class of digraphs D whose only open neighbourhood locating -dominating set consists of the whole set of vertices, in other words, gamma OL(D) is equal to the order of D. We call those digraphs extremal. By considering digraphs with loops allowed, our definition also applies to the related (and more widely studied) concept of identifying codes. We extend previous studies from the literature for both open neighbourhood locating -dominating sets and identifying codes of both undirected and directed graphs. These results all correspond to studying open neighbourhood locating -dominating sets on special classes of digraphs. To do so, we prove general structural properties of extremal digraphs, and we describe how they can all be constructed. We then use these properties to give new proofs of several known results from the literature. We also give a recursive and constructive characterization of the extremal di -trees (digraphs whose underlying undirected graph is a tree). (c) 2023 Elsevier B.V. All rights reserved.
In a graph G, a set C subset of V (G) is an identifying code if, for all vertices v in G, the sets N[v] boolean AND C are all nonempty and pairwise distinct, where N[v] denotes the closed neighbourhood of v. We focus ...
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In a graph G, a set C subset of V (G) is an identifying code if, for all vertices v in G, the sets N[v] boolean AND C are all nonempty and pairwise distinct, where N[v] denotes the closed neighbourhood of v. We focus on the minimum density of identifying codes of infinite hexagonal grids Hk with k rows, denoted by d*(Hk), and present optimal solutions for k <= 5. Using the discharging method, we also prove a lower bound in terms of maximum degree for the minimum-density identifying codes of well-behaved infinite graphs. We prove that d*(H2) = 9/20, d*(H3) = 6/13 approximate to 0.4615, d*(H4) = 7/16 = 0.4375 and d*(H5) = 11/25 = 0.44. We also prove that H2 has a unique periodic identifying code with minimum density.
Given an integer l >= 1, a (1, = 3. Then we give a characterization so that a line digraph of a digraph different from a directed cycle of length 4 and minimum in-degree one admits a (1, <= 2)-identifying code. ...
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Given an integer l >= 1, a (1, <= l)-identifying code in a digraph is a dominating subset C of vertices such that all distinct subsets of vertices of cardinality at most l have distinct closed in-neighborhoods within C. In this paper, we prove that every line digraph of minimum in-degree one does not admit a (1, <= l)-identifying code for l >= 3. Then we give a characterization so that a line digraph of a digraph different from a directed cycle of length 4 and minimum in-degree one admits a (1, <= 2)-identifying code. The identifying number of a digraph D, (gamma) over right arrow D-ID(D), is the minimum size of all the identifying codes of D. We establish for digraphs without digons with both vertices of in-degree one that (gamma) over right arrow (ID) (LD) is lower bounded by the number of arcs of D minus the number of vertices with out-degree at least one. Then we show (gamma) over right arrow (ID)(LD) attains the equality for a digraph having a 1-factor with minimum in-degree two and without digons with both vertices of in-degree two. We finish by giving an algorithm to construct identifying codes in oriented digraphs with minimum in-degree at least two and minimum out-degree at least one. (C) 2020 Elsevier Inc. All rights reserved.
The problems of determining the minimum-sized identifying, locating-dominating and open locating-dominating codes of an input graph are special search problems that are challenging from both theoretical and computatio...
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The problems of determining the minimum-sized identifying, locating-dominating and open locating-dominating codes of an input graph are special search problems that are challenging from both theoretical and computational viewpoints. In these problems, one selects a dominating set C of a graph G such that the vertices of a chosen subset of V (G) (i.e. either V (G) n C or V (G) itself) are uniquely determined by their neighborhoods in C. A typical line of attack for these problems is to determine tight bounds for the minimum codes in various graph classes. In this work, we present tight lower and upper bounds for all three types of codes for block graphs (i.e. diamond-free chordal graphs). Our bounds are in terms of the number of maximal cliques (or blocks) of a block graph and the order of the graph. Two of our upper bounds verify conjectures from the literature with one of them being now proven for block graphs in this article. As for the lower bounds, we prove them to be linear in terms of both the number of blocks and the order of the block graph. We provide examples of families of block graphs whose minimum codes attain these bounds, thus showing each bound to be tight.
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