Paper
21 September 2006 An optimal policy based on the genetic algorithm for the dynamic threshold of the optical network
Hongying Zhu, Zichun Le, Wen Dong, Minglei Fu
Author Affiliations +
Proceedings Volume 6353, Optical Transmission, Switching, and Subsystems IV; 63530P (2006) https://doi.org/10.1117/12.688635
Event: Asia-Pacific Optical Communications, 2006, Gwangju, South Korea
Abstract
The complete partitioning policy (CP) for the wavelength resource in optical networks is now widely focused on. The dynamic threshold is one of the ways to make CP policy more efficient. Furthermore, an optimized threshold will be better for reducing the blocking probability and improving the utilization of the wavelength resource. Hence, the genetic algorithm is selected as the optimal policy on virtue of its excellent global search performance for getting optimized value of the dynamic threshold. Moreover, a maximal threshold as the high limit for the dynamic threshold is needed to be decided for making wavelengths shared between different wavelength classes, because the class with higher priority can share its wavelengths with the lower one after its own call setups are satisfied. Therefore, a neural network predictor that can predict the number of the next call setup is designed on the basis of the genetic algorithm to solve this problem. The values of the dynamic threshold and the maximal threshold are calculated, and the simulation results show that they take good effect in reducing the blocking probability and improving the utilization of the wavelength resource.
© (2006) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Hongying Zhu, Zichun Le, Wen Dong, and Minglei Fu "An optimal policy based on the genetic algorithm for the dynamic threshold of the optical network", Proc. SPIE 6353, Optical Transmission, Switching, and Subsystems IV, 63530P (21 September 2006); https://doi.org/10.1117/12.688635
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KEYWORDS
Genetic algorithms

Neural networks

Optical networks

Neurons

Aluminum

Bismuth

Evolutionary algorithms

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