A proactive restoration strategy for optical cloud networks based on failure prediction

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dc.creatorCarlos Natalino da Silva
dc.creatorFrederico Gualberto Ferreira Coelho
dc.creatorAntonio de Padua Braga
dc.creatorLena Wosinska
dc.creatorPaolo Monti
dc.creatorGustavo Lacerda
dc.date.accessioned2025-04-15T15:02:38Z
dc.date.accessioned2025-09-09T00:12:32Z
dc.date.available2025-04-15T15:02:38Z
dc.date.issued2018
dc.identifier.doi10.1109/ICTON.2018.8473938
dc.identifier.urihttps://hdl.handle.net/1843/81606
dc.languageeng
dc.publisherUniversidade Federal de Minas Gerais
dc.relation.ispartof20th International Conference on Transparent Optical Networks (ICTON)
dc.rightsAcesso Aberto
dc.subjectAprendizado do computador
dc.subjectProgramação orientada a objetos (Computação)
dc.subject.otherProactive recovery, Failure prediction, Resiliency, Cloud services, Availability, Restoration, Softwaredefined networking (SDN), Orchestration, Cloud service relocation
dc.titleA proactive restoration strategy for optical cloud networks based on failure prediction
dc.typeArtigo de evento
local.description.resumoFailure prediction based on the anomaly detection/forecasting is becoming a reality thanks to the introduction of machine learning techniques. The orchestration layer can leverage on this new feature to proactively reconfigure cloud services that might find themselves traversing an element that is about to fail. As a result, the number of cloud service interruptions can be reduced with beneficial effects in terms of cloud service availability. Based on the above intuition, this paper presents an orchestration strategy for optical cloud networks able to reconfigure vulnerable cloud services (i.e., the ones that would be disrupted if a predicted failure happens) before an actual failure takes place. Simulation results demonstrate that, with a single link failure scenario, proactive restoration can lead to up to 97% less cloud services having to be relocated. This result brings considerable benefits in terms of cloud service availability, especially in low load conditions. It is also shown that these improvements come with almost no increase in the cloud service blocking probability performance, i.e., resource efficiency is not impacted.
local.publisher.countryBrasil
local.publisher.departmentENG - DEPARTAMENTO DE ENGENHARIA ELETRÔNICA
local.publisher.initialsUFMG
local.url.externahttps://ieeexplore.ieee.org/document/8473938

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