Random subgraphs make identification affordable

An identifying code of a graph is a dominating set which uniquely determines all the vertices by their neighborhood within the code. Whereas graphs with large minimum degree have small domination number, this is not the case for the identifying code number (the size of a smallest identifying code),...

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Detalles Bibliográficos
Autores: Foucaud, Florent, Perarnau Llobet, Guillem|||0000-0002-1953-9511, Serra Albó, Oriol|||0000-0001-8561-4631
Tipo de recurso: artículo
Fecha de publicación:2017
País:España
Institución:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2117/112330
Acceso en línea:https://hdl.handle.net/2117/112330
https://dx.doi.org/10.4310/JOC.2017.v8.n1.a3
Access Level:acceso abierto
Palabra clave:Graph theory
identifying codes
random subgraphs
Grafs, Teoria de
Classificació AMS::05 Combinatorics::05C Graph theory
Àrees temàtiques de la UPC::Matemàtiques i estadística::Matemàtica discreta::Combinatòria
Descripción
Sumario:An identifying code of a graph is a dominating set which uniquely determines all the vertices by their neighborhood within the code. Whereas graphs with large minimum degree have small domination number, this is not the case for the identifying code number (the size of a smallest identifying code), which indeed is not even a monotone parameter with respect to graph inclusion. We show that for every large enough ¿¿, every graph GG on nn vertices with maximum degree ¿¿ and minimum degree d=clog¿d=clog¿¿, for some constant c>0c>0, contains a large spanning subgraph which admits an identifying code with size O(nlog¿d)O(nlog¿¿d). In particular, if d=T(n)d=T(n), then GG has a dense spanning subgraph with identifying code O(logn)O(log¿n), namely, of asymptotically optimal size. The subgraph we build is created using a probabilistic approach, and we use an interplay of various random methods to analyze it. Moreover we show that the result is essentially best possible, both in terms of the number of deleted edges and the size of the identifying code.