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Memorias de investigación
Ponencias en congresos:
Towards an autonomic Bayesian fault diagnosis service for SDN environments based on a big data infrastructure
Año:2018
Áreas de investigación
  • Telemática
Datos
Descripción
Software Defined Networks (SDN) are gaining momentum as a solution for current and future networking issues. Its programmability and centralised control enables a more dynamic management of the network. But this feature introduces the cost of a potential increase in failures, since every modification introduced on the control plane is a new possibility for failures to appear and cause a decrement of the quality for the offered service. Following a classical approach, this kind of problems could be solved increasing the number of high skilled human operators, which would dramatically increase network operation cost. Our approach is to apply Machine Learning and Data Analysis for monitoring and diagnosis SDN networks with the goal of automating these tasks. In this paper, we present an architecture for a self-diagnosis service which is deployed on top of a SDN management platform. In addition, a prototype of the proposed service with different diagnosis models for SDN networks has been developed. The evaluation shows encouraging results which will be explored in future works.
Internacional
Si
Nombre congreso
2018 Fifth International Conference on Software Defined Systems (SDS)
Tipo de participación
960
Lugar del congreso
Barcelona
Revisores
Si
ISBN o ISSN
978-1-5386-5900-7
DOI
10.1109/SDS.2018.8370415
Fecha inicio congreso
23/04/2018
Fecha fin congreso
26/04/2018
Desde la página
7
Hasta la página
13
Título de las actas
2018 Fifth International Conference on Software Defined Systems (SDS)
Esta actividad pertenece a memorias de investigación
Participantes
  • Autor: Fernando Benayas De los Santos (UPM)
  • Autor: Alvaro Carrera Barroso (UPM)
  • Autor: Carlos Angel Iglesias Fernandez (UPM)
Grupos de investigación, Departamentos, Centros e Institutos de I+D+i relacionados
  • Creador: Grupo de Investigación: Grupo de Sistemas Inteligentes
  • Departamento: Ingeniería de Sistemas Telemáticos
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