Information theory perspective on network robustness

dc.creatorTiago A. Schieber
dc.creatorLaura Carpi
dc.creatorAlejandro C. Frery
dc.creatorOsvaldo A. Rosso
dc.creatorPanos M. Pardalos
dc.creatorMartín G. Ravetti
dc.date.accessioned2023-03-16T12:11:14Z
dc.date.accessioned2025-09-09T00:34:06Z
dc.date.available2023-03-16T12:11:14Z
dc.date.issued2016
dc.identifier.doi10.1016/j.physleta.2015.10.055
dc.identifier.issn03759601
dc.identifier.urihttps://hdl.handle.net/1843/50945
dc.languagepor
dc.publisherUniversidade Federal de Minas Gerais
dc.relation.ispartofPhysics Letters A
dc.rightsAcesso Aberto
dc.subjectTeoria da informação
dc.subject.otherNetwork robustness
dc.subject.otherComplex networks
dc.subject.otherInformation theory
dc.titleInformation theory perspective on network robustness
dc.typeArtigo de periódico
local.citation.epage364
local.citation.issue2016
local.citation.spage359
local.citation.volume380
local.description.resumoA crucial challenge in network theory is the study of the robustness of a network when facing a sequence of failures. In this work, we propose a dynamical definition of network robustness based on Information Theory, that considers measurements of the structural changes caused by failures of the network’s components. Failures are defined here as a temporal process defined in a sequence. Robustness is then evaluated by measuring dissimilarities between topologies after each time step of the sequence, providing a dynamical information about the topological damage. We thoroughly analyze the efficiency of the method in capturing small perturbations by considering different probability distributions on networks. In particular, we find that distributions based on distances are more consistent in capturing network structural deviations, as better reflect the consequences of the failures. Theoretical examples and real networks are used to study the performance of this methodology.
local.publisher.countryBrasil
local.publisher.departmentFCE - DEPARTAMENTO DE CIÊNCIAS ADMINISTRATIVAS
local.publisher.departmentICX - DEPARTAMENTO DE CIÊNCIA DA COMPUTAÇÃO
local.publisher.initialsUFMG
local.url.externahttps://reader.elsevier.com/reader/sd/pii/S0375960115009275?token=946CB1931BC133FB87866F89313839B184BE38FF75F1C83A1E2E32137EEDF7786B796F27E26C465BE6C3DE596204A93D&originRegion=us-east-1&originCreation=20230316115909

Arquivos

Pacote original

Agora exibindo 1 - 1 de 1
Carregando...
Imagem de Miniatura
Nome:
Information theory perspective on network robustness Elsevier Enhanced Reader.pdf
Tamanho:
3.24 MB
Formato:
Adobe Portable Document Format

Licença do pacote

Agora exibindo 1 - 1 de 1
Carregando...
Imagem de Miniatura
Nome:
License.txt
Tamanho:
1.99 KB
Formato:
Plain Text
Descrição: