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<p>This study investigates the optimization of lightpath selection and traffic management in Wavelength Division Multiplexing (WDM) networks with a Ring topology. By employing the Heuristic Adaptation Algorithm (HAA) and Yen’s K-Shortest Path Algorithm, we propose a dynamic traffic allocation framework tailored to the unique characteristics of Ring topology. The framework effectively optimizes key performance metrics such as energy consumption, throughput, packet delivery ratio, and congestion levels under both slow-changing and fast-changing traffic scenarios. The integration of a Multilayer Perceptron (MLP) model significantly enhances the predictive accuracy of performance metrics, achieving a correlation coefficient of 0.9972, with minimal errors (Mean Absolute Error: 2.8444; Root Mean Squared Error: 5.0271). The results reveal that the proposed framework achieves a 92.5% lightpath utilization rate while maintaining high energy efficiency, even with increasing traffic demand. The findings emphasize the trade-offs between clockwise and counterclockwise routing in Ring networks, offering a cost-effective and scalable solution for dynamic traffic environments.</p>

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Holistic framework for optical network efficiency: logical topology revamping in the presence of dynamic traffic demand for ring physical topology networks

  • 期刊论文

  • 发表日期：

    2025年5月4日

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  • Shivranjani Bharatbhai Gajjar,
  • Vivekanand Mishra

摘要

This study investigates the optimization of lightpath selection and traffic management in Wavelength Division Multiplexing (WDM) networks with a Ring topology. By employing the Heuristic Adaptation Algorithm (HAA) and Yen’s K-Shortest Path Algorithm, we propose a dynamic traffic allocation framework tailored to the unique characteristics of Ring topology. The framework effectively optimizes key performance metrics such as energy consumption, throughput, packet delivery ratio, and congestion levels under both slow-changing and fast-changing traffic scenarios. The integration of a Multilayer Perceptron (MLP) model significantly enhances the predictive accuracy of performance metrics, achieving a correlation coefficient of 0.9972, with minimal errors (Mean Absolute Error: 2.8444; Root Mean Squared Error: 5.0271). The results reveal that the proposed framework achieves a 92.5% lightpath utilization rate while maintaining high energy efficiency, even with increasing traffic demand. The findings emphasize the trade-offs between clockwise and counterclockwise routing in Ring networks, offering a cost-effective and scalable solution for dynamic traffic environments.