Zero forcing in iterated line digraphs

Zero forcing is a propagation process on a graph, or digraph, defined in linear algebra to provide a bound for the minimum rank problem. Independently, zero forcing was introduced in physics, computer science and network science, areas where line digraphs are frequently used as models. Zero forcing is also related to power domination, a propagation process that models the monitoring of electrical power networks. In this paper we study zero forcing in iterated line digraphs and provide a relationship between zero forcing and power domination in line digraphs. In particular, for regular iterated line digraphs we determine the minimum rank/maximum nullity, zero forcing number and power domination number, and provide constructions to attain them. We conclude that regular iterated line digraphs present optimal minimum rank/maximum nullity, zero forcing number and power domination number, and apply our results to determine those parameters on some families of digraphs often used in applications

Distance-layer structure of the De Bruijn and Kautz digraphs: analysis and application to deflection routing

This is the peer reviewed version of the following article: Fàbrega, J.; Martí, J.; Muñoz, X. Distance-layer structure of the De Bruijn and Kautz digraphs: analysis and application to deflection routing. "Networks", 29 Juliol 2023, which has been published in final form at https://onlinelibrary.wiley.com/doi/10.1002/net.22177. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions. This article may not be enhanced, enriched or otherwise transformed into a derivative work, without express permission from Wiley or by statutory rights under applicable legislation. Copyright notices must not be removed, obscured or modified. The article must be linked to Wiley’s version of record on Wiley Online Library and any embedding, framing or otherwise making available the article or pages thereof by third parties from platforms, services and websites other than Wiley Online Library must be prohibited.In this article, we present a detailed study of the reach distance-layer structure of the De Bruijn and Kautz digraphs, and we apply our analysis to the performance evaluation of deflection routing in De Bruijn and Kautz networks. Concerning the distance-layer structure, we provide explicit polynomial expressions, in terms of the degree of the digraph, for the cardinalities of some relevant sets of this structure. Regarding the application to defection routing, and as a consequence of our polynomial description of the distance-layer structure, we formulate explicit expressions, in terms of the degree of the digraph, for some probabilities of interest in the analysis of this type of routing. De Bruijn and Kautz digraphs are fundamental examples of digraphs on alphabet and iterated line digraphs. If the topology of the network under consideration corresponds to a digraph of this type, we can perform, in principle, a similar vertex layer description.Partially supported by the Ministerio de Ciencia e Innovación/Agencia Estatal de Investigación, Spain, and the European Regional Development Fund under project PGC2018-095471-B-I00; and by AGAUR from the Catalan Government under project 2017SGR-1087.Peer ReviewedPostprint (author's final draft

Failed power domination on graphs

Let G be a simple graph with vertex set V and edge set E, and let S ⊆ V . The sets Pi (S), i ≥ 0, of vertices monitored by S at the i th step are given by P0(S) = N[S] and Pi+1(S) = Pi (S) {w : {w} = N[v]\Pi (S) for some v ∈ Pi (S)}. If there exists j such that Pj (S) = V , then S is called a power dominating set, PDS, of G. Otherwise, S is a failed power dominating set, FPDS. The power domination number of a simple graph G, denoted γp(G) gives the minimum number of measurement devices known as phasor measurement units (PMUs) required to observe a power network represented by G, and is the minimum cardinality of any PDS of G. The failed power domination number of G, ¯γp(G), is the maximum cardinality of any FPDS of G, and represents the maximum number of PMUs that could be placed on a given power network represented by G, but fail to observe the full network. As a consequence, ¯γp(G)+1 gives the minimum number of PMUs necessary to successfully observe the full network no matter where they are placed. We prove that ¯γp(G) is NP-hard to compute, determine graphs in which every vertex is a PDS, and compare ¯γp(G) to similar parameters

3-Factor-criticality in double domination edge critical graphs

A vertex subset $S$ of a graph $G$ is a double dominating set of $G$ if $|N[v]\cap S|\geq 2$ for each vertex $v$ of $G$, where $N[v]$ is the set of the vertex $v$ and vertices adjacent to $v$. The double domination number of $G$, denoted by $\gamma_{\times 2}(G)$, is the cardinality of a smallest double dominating set of $G$. A graph $G$ is said to be double domination edge critical if $\gamma_{\times 2}(G+e)<\gamma_{\times 2}(G)$ for any edge $e \notin E$. A double domination edge critical graph $G$ with $\gamma_{\times 2}(G)=k$ is called $k$-$\gamma_{\times 2}(G)$-critical. A graph $G$ is $r$-factor-critical if $G-S$ has a perfect matching for each set $S$ of $r$ vertices in $G$. In this paper we show that $G$ is 3-factor-critical if $G$ is a 3-connected claw-free $4$-$\gamma_{\times 2}(G)$-critical graph of odd order with minimum degree at least 4 except a family of graphs.Comment: 14 page

Proceedings of the 3rd International Workshop on Optimal Networks Topologies IWONT 2010

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