Reconstruction of networks from their betweenness centrality

In this paper we study the reconstruction of a network topology from the values of its betweenness centrality, a measure of the influence of each of its nodes in the dissemination of information over the network. We consider a simple metaheuristic, simulated annealing, as the combinatorial optimizat...

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Detalhes bibliográficos
Autores: Comellas Padró, Francesc de Paula|||0000-0003-4523-0240, Paz-Sánchez, Juan
Tipo de documento: artigo
Data de publicação:2008
País:España
Recursos:Universitat Politècnica de Catalunya (UPC)
Repositório:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglês
OAI Identifier:oai:upcommons.upc.edu:2117/1474
Acesso em linha:https://hdl.handle.net/2117/1474
Access Level:Acceso aberto
Palavra-chave:Combinatorics
Complex networks
Betweennes centrality
Combinacions (Matemàtica)
Classificació AMS::05 Combinatorics
Descrição
Resumo:In this paper we study the reconstruction of a network topology from the values of its betweenness centrality, a measure of the influence of each of its nodes in the dissemination of information over the network. We consider a simple metaheuristic, simulated annealing, as the combinatorial optimization method to generate the network from the values of the betweenness centrality. We compare the performance of this technique when reconstructing different categories of networks –random, regular, small-world, scale-free and clustered–. We show that the method allows an exact reconstruction of small networks and leads to good topological approximations in the case of networks with larger orders. The method can be used to generate a quasi-optimal topology fora communication network from a list with the values of the maximum allowable traffic for each node.