中国邮电高校学报(英文) ›› 2022, Vol. 29 ›› Issue (6): 46-52.doi: 10.19682/j.cnki.1005-8885.2022.1023

• Special Topic: Optical Communication and Artificial Intelligence • 上一篇    下一篇

Prediction-based dynamic routing intelligent algorithm in power optical communication network

Guo Xuerang,Li Feng,Zhu Bohan,Zhang Zhijun,Guo Qingrui,Yang Huiting   

  1. 1. Electric Power Research Institute, State Grid Xinjiang Electric Power Co. , Ltd. , Urumqi 830000, China   2. State Key Laboratory of Information Photonics and Optical Communications, Beijing University of Posts and Telecommunications, Beijing 100876, China   3. Dispatching and Control Center, State Grid Xinjiang Electric Power Co. , Ltd. , Urumqi 830000, China
  • 收稿日期:2022-10-20 修回日期:2022-11-16 出版日期:2022-12-30 发布日期:2022-12-30
  • 通讯作者: Zhu Bohan E-mail:Zhubh@bupt.edu.cn
  • 基金资助:

    This work was supported by the National Natural Science Foundation of China (62021005).

Prediction-based dynamic routing intelligent algorithm in power optical communication network

Guo Xuerang,Li Feng,Zhu Bohan,Zhang Zhijun,Guo Qingrui,Yang Huiting   

  1. 1. Electric Power Research Institute, State Grid Xinjiang Electric Power Co. , Ltd. , Urumqi 830000, China   2. State Key Laboratory of Information Photonics and Optical Communications, Beijing University of Posts and Telecommunications, Beijing 100876, China   3. Dispatching and Control Center, State Grid Xinjiang Electric Power Co. , Ltd. , Urumqi 830000, China
  • Received:2022-10-20 Revised:2022-11-16 Online:2022-12-30 Published:2022-12-30
  • Contact: Zhu Bohan E-mail:Zhubh@bupt.edu.cn
  • Supported by:
    This work was supported by the National Natural Science Foundation of China (62021005).

摘要:

New energy power generation equipment has the characteristics of diurnal, perturbative, seasonal, and periodic power generation, which makes new power optical communication network ( POCN ) more dynamic and changeable. This is directly reflected in the dynamics of the link risk and service importance of the POCN. In this paper, aiming at the problem of the dynamic importance of service in POCN, and the resulting power optical communication network reliability decline problem, a new energy POCN dynamic routing intelligence algorithm based on service importance prediction is proposed. Based on the short-term power generation of new energy power station, the importance of each service and the risk degree of each link are predicted. Link weights are dynamically adjusted, and k-shortest path ( KSP) algorithm is used to calculate route results. When network resources are insufficient, low-importance services can give way to prevent a large number of high-importance services from being blocked. Simulation results show that compared with the traditional KSP algorithm, the prediction-based dynamic routing intelligent ( P-DRI) algorithm can reduce the service blocking probability by 55.59% , and reduce the average importance of blocking services by 44.77% at the cost of about 6.17% of the calculation delay.

关键词:

new power optical communication network (POCN), traffic diversion, new energy power generation, network risk degree

Abstract: New energy power generation equipment has the characteristics of diurnal, perturbative, seasonal, and periodic power generation, which makes new power optical communication network ( POCN ) more dynamic and changeable. This is directly reflected in the dynamics of the link risk and service importance of the POCN. In this paper, aiming at the problem of the dynamic importance of service in POCN, and the resulting power optical communication network reliability decline problem, a new energy POCN dynamic routing intelligence algorithm based on service importance prediction is proposed. Based on the short-term power generation of new energy power station, the importance of each service and the risk degree of each link are predicted. Link weights are dynamically adjusted, and k-shortest path ( KSP) algorithm is used to calculate route results. When network resources are insufficient, low-importance services can give way to prevent a large number of high-importance services from being blocked. Simulation results show that compared with the traditional KSP algorithm, the prediction-based dynamic routing intelligent ( P-DRI) algorithm can reduce the service blocking probability by 55.59% , and reduce the average importance of blocking services by 44.77% at the cost of about 6.17% of the calculation delay.

Key words: new power optical communication network (POCN), traffic diversion, new energy power generation, network risk degree

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