Abstract
High degree of heterogeneity of future optical networks, such as services with different quality-of-transmission requirements, modulation formats and switching techniques, will pose a challenge for the control and optimization of different parameters. Incorporation of cognitive techniques can help to solve this issue by realizing a network that can observe, act, learn and optimize its performance, taking into account end-to-end goals.
In this letter we present the approach of cognition applied to heterogeneous optical networks developed in the framework of the EU project CHRON: Cognitive Heterogeneous Reconfigurable Optical Network. We focus on the approaches developed in the project for optical performance monitoring, which enable the feedback from the physical layer to the cognitive decision system by providing accurate description of the performance of the established lightpaths.
In this letter we present the approach of cognition applied to heterogeneous optical networks developed in the framework of the EU project CHRON: Cognitive Heterogeneous Reconfigurable Optical Network. We focus on the approaches developed in the project for optical performance monitoring, which enable the feedback from the physical layer to the cognitive decision system by providing accurate description of the performance of the established lightpaths.
Original language | English |
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Title of host publication | Proceedings of ICTON 2013 |
Number of pages | 4 |
Publisher | IEEE |
Publication date | 2013 |
ISBN (Print) | 978-1-4799-0683-3 |
DOIs | |
Publication status | Published - 2013 |
Event | 15th International Conference on Transparent Optical Networks (ICTON) - Cartagena, Spain Duration: 23 Jun 2013 → 27 Jun 2013 http://www.ait.upct.es/icton2013/ |
Conference
Conference | 15th International Conference on Transparent Optical Networks (ICTON) |
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Country/Territory | Spain |
City | Cartagena |
Period | 23/06/2013 → 27/06/2013 |
Internet address |
Keywords
- Optical networks
- Cognition
- Dynamic optical networks
- Optical performance monitoring