2019
DOI: 10.1049/iet-net.2018.5107
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Risk‐aware last‐minute data backup in inter‐datacenter networks

Abstract: Network failure caused by disasters (both natural and man-made like earthquakes, floods, cyclones, electromagnetic pulse attacks etc.) result in communication disruption and huge amounts of data loss in the backbone datacenter (DC) networks. To prevent such large-scale network disruptions and quickly resume connectivity after the disaster, network operators require improved and efficient data-transfer algorithms in geographically distributed (geo-distributed) optical inter-DC networks. Minimising loss of infra… Show more

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Cited by 5 publications
(3 citation statements)
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“…When the 2 conditions of Eqs. (10) and (11) are satisfied, the function ( , ) V G D reaches the global maximum, i.e., the LSTM-GAN reaches an equilibrium: G data ( ) ( )…”
Section: Lstm-gan Based Data Recovery Model For Power Systemmentioning
confidence: 99%
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“…When the 2 conditions of Eqs. (10) and (11) are satisfied, the function ( , ) V G D reaches the global maximum, i.e., the LSTM-GAN reaches an equilibrium: G data ( ) ( )…”
Section: Lstm-gan Based Data Recovery Model For Power Systemmentioning
confidence: 99%
“…The significant amount of data in the data disaster recovery time also has a significant impact. With the advent of the "Big Data Era" and "Cloud Era", traditional data disaster recovery solutions have failed to catch up with the pace of the times [8][9][10].…”
Section: Introductionmentioning
confidence: 99%
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