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- W3112990759 abstract "Routing, Modulation Level and Spectrum Assignment (RMLSA) are some of the main problems studied in elastic optical networks. This work focuses on the study of guard band selection, with one or more free slots between the circuits, which are used in the solutions of the RMLSA problem in order to reduce the interference between adjacent circuits in the spectrum optical. In this context, a new approach, called ADVANCE, which uses a convolutional neural network to adaptive guard band selection is proposed. A proposal performance is compared to other adaptive proposals: AGBA, GBUN and UTOPIAN. The proposal achieves a reduction in the bandwidth blocking probability of at least 86.56% relative to AGBA, 84.60% relative to GBUN and 73.26% relative to UTOPIAN." @default.
- W3112990759 created "2020-12-21" @default.
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- W3112990759 date "2020-10-11" @default.
- W3112990759 modified "2023-09-25" @default.
- W3112990759 title "An Adaptive Guard Band Selection based on Convolutional Neural Network" @default.
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- W3112990759 doi "https://doi.org/10.1109/smc42975.2020.9283197" @default.
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