Memorias de investigación
Artículos en revistas:
A Bayesian Argumentation Framework for Distributed Fault Diagnosis in Telecommunication Networks
Año:2019
Áreas de investigación
  • Telemática
Datos
Descripción
Traditionally, fault diagnosis in telecommunication network management is carried out by humans who use software support systems. The phenomenal growth in telecommunication networks has nonetheless triggered the interest in more autonomous approaches, capable of coping with emergent challenges such as the need to diagnose faults? root causes under uncertainty in geographically-distributed environments, with restrictions on data privacy. In this paper, we present a framework for distributed fault diagnosis under uncertainty based on an argumentative framework for multi-agent systems. In our approach, agents collaborate to reach conclusions by arguing in unpredictable scenarios. The observations collected from the network are used to infer possible fault root causes using Bayesian networks as causal models for the diagnosis process. Hypotheses about those fault root causes are discussed by agents in an argumentative dialogue to achieve a reliable conclusion. During that dialogue, agents handle the uncertainty of the diagnosis process, taking care of keeping data privacy among them. The proposed approach is compared against existing alternatives using benchmark multi-domain datasets. Moreover, we include data collected from a previous fault diagnosis system running in a telecommunication network for one and a half years. Results show that the proposed approach is suitable for the motivational scenario.
Internacional
Si
JCR del ISI
Si
Título de la revista
Sensors
ISSN
1424-8220
Factor de impacto JCR
3,275
Información de impacto
JCR 2019
Volumen
19
DOI
10.3390/s19153408
Número de revista
15
Desde la página
3408
Hasta la página
22
Mes
SIN MES
Ranking
Q1
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Participantes
Grupos de investigación, Departamentos, Centros e Institutos de I+D+i relacionados
  • Creador: Departamento: Ingeniería de Sistemas Telemáticos