Cognitive algorithm using fuzzy reasoning for software-defined optical network

Cognitive algorithm using fuzzy reasoning for software-defined optical network We propose a cognitive algorithm based on Fuzzy C-Means (FCM) technique for the learning and decision-making functionalities of software-defined optical networks (SDONs). SDON is a new optical network paradigm where the control plane is decoupled from the data plane, thus providing a degree of software programmability to the network. Our proposal is to add the FCM algorithm to the SDON control plane in order to achieve a better network performance, when compared with a non-cognitive control plane. In this context, we illustrate the use of the FCM algorithm for determining, in real time and autonomously, the modulation format of high-speed flexible rate transponders in accordance with the quality of transmission of optical channels. The performance of this FCM algorithm is evaluated via computational simulations for a long-haul network and compared to the case-based reasoning (CBR) algorithm, which is commonly used in optical cognitive networks. We demonstrate that FCM outperforms CBR in both fastness and error avoidance, achieving 100 % of successful classifications, being two orders of magnitude faster. Additionally, we propose a definition of cognitive optical networking and an architecture for the SDON control plane including the FCM engine. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Photonic Network Communications Springer Journals

Cognitive algorithm using fuzzy reasoning for software-defined optical network

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Publisher
Springer US
Copyright
Copyright © 2016 by Springer Science+Business Media New York
Subject
Computer Science; Computer Communication Networks; Electrical Engineering; Characterization and Evaluation of Materials
ISSN
1387-974X
eISSN
1572-8188
D.O.I.
10.1007/s11107-016-0628-1
Publisher site
See Article on Publisher Site

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