Cognitive Management and Control for Wavelength Assignment and Reconfiguration in Optical Networks
Name
icc2019.pdf
Description
Accepted version
Size
1.31 MB
Format
Adobe PDF
Checksum (MD5)
34032830cb3383629a781037572cb1fb
Author(s)
Zheng, Anny Xijia
Chan, Vincent
Shannon, Claude E
Date Issued
July 2019
Journal
2019 IEEE International Conference on Communications (ICC)
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
Zheng, Anny Xijia et al. "Cognitive Management and Control for Wavelength Assignment and Reconfiguration in Optical Networks." 2019 IEEE International Conference on Communications, May 2019, Shanghai, China, July 2019. © 2019 IEEE
Version
Author's final manuscript
Abstract
We address the design of fast wavelength assignment and reconfiguration using cognitive management and control that can quickly and accurately adapt to the operating conditions for optical networks. The traffic detection performances of two Bayesian estimators and a stopping-trial (sequential) estimator are examined based on the transient behaviors of networks. The stopping-trial estimator has the fastest response time to the changes of traffic arrival statistics. We propose a wavelength reconfiguration algorithm with continuous assessment where the system reconfigures whenever it deems necessary. The reconfiguration can involve addition or subtraction of multiple wavelengths. Using the fastest detection and reconfiguration algorithm can reduce queueing delays during traffic surges without over provisioning and thus can reduce network capital expenditure and prevent waste of resources upon erroneous decision on occurrence of surges.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1109/icc.2019.8761874
