A bayesian argumentation framework for distributed fault diagnosis in telecommunication networks

Carrera Barroso, Álvaro and Alonso, Eduardo and Iglesias Fernández, Carlos Ángel (2019). A bayesian argumentation framework for distributed fault diagnosis in telecommunication networks. "Sensors", v. 19 (n. 15); pp. 1-22. ISSN 1424-8220. https://doi.org/10.3390/s19153408.

Description

Title: A bayesian argumentation framework for distributed fault diagnosis in telecommunication networks
Author/s:
  • Carrera Barroso, Álvaro
  • Alonso, Eduardo
  • Iglesias Fernández, Carlos Ángel
Item Type: Article
Título de Revista/Publicación: Sensors
Date: August 2019
ISSN: 1424-8220
Volume: 19
Subjects:
Freetext Keywords: argumentation; Bayesian; distributed; fault diagnosis; federation; future Internet; multi-agent system
Faculty: E.T.S.I. Telecomunicación (UPM)
Department: Ingeniería de Sistemas Telemáticos
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

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.

Funding Projects

TypeCodeAcronymLeaderTitle
Government of SpainTEC2015-68284-RSEMOLACarlos A. Iglesias; Tomás RoblesTecnologías de Análisis de Sentimientos y emociones para agentes sociales empáticos en inteligencia ambiental
Universidad Politécnica de MadridEE.BB.2013UnspecifiedUnspecifiedUPM grant for Short Stays

More information

Item ID: 67507
DC Identifier: https://oa.upm.es/67507/
OAI Identifier: oai:oa.upm.es:67507
DOI: 10.3390/s19153408
Official URL: https://www.mdpi.com/1424-8220/19/15/3408
Deposited by: Memoria Investigacion
Deposited on: 04 Sep 2021 09:32
Last Modified: 04 Sep 2021 09:32
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