Journal
JOURNAL OF LIGHTWAVE TECHNOLOGY
Volume 31, Issue 6, Pages 942-951Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JLT.2013.2240257
Keywords
Case-based reasoning (CBR); cognitive networks; impairment-aware networking; quality of transmission (QoT); wavelength-routed optical network (WRON)
Funding
- CHRON (Cognitive Heterogeneous Reconfigurable Optical Network) project
- European Community [258644]
- Council of Education of the Regional Government of Castilla-Leon
- European Social Fund
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We propose a cognitive Quality of Transmission (QoT) estimator for classifying lightpaths into high or low quality categories in impairment-aware wavelength-routed optical networks. The technique is based on Case-Based Reasoning (CBR), an artificial intelligence technique which solves new problems by exploiting previous experiences, which are stored on a knowledge base. We also show that by including learning and forgetting techniques, the underlying knowledge base can be optimized, thus leading to a significant reduction on the computing time for on-line operation. The performance of the cognitive estimator is evaluated in a long haul and in an ultra-long haul network, and we demonstrate that it achieves more than 98% successful classifications, and that it is up to four orders of magnitude faster when compared with a non-cognitive QoT estimator, the Q-Tool.
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