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Boyang Lin

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Proceedings Article | 27 March 2022 Paper

Educational experimental platform for engineering training in AI-assisted optical networks for data center

Ziyi Xi, Boyang Lin, Rentao Gu, Zeyuan Yang, Yuefeng Ji

Proceedings Volume 12169, 121695E (2022) https://doi.org/10.1117/12.2624364

KEYWORDS: Data centers, Optical networks, Networks, Evolutionary algorithms, Network architectures, Control systems, Human-machine interfaces, Artificial intelligence, Algorithm development, Visualization

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With the rapid development of optical network for data center techniques and artificial intelligent algorithms, it’s harder to train relevant professionals. Experimental course plays an important role for students to deepen understanding of complex theoretical knowledge. However, existing SDN-based experimental platforms face two challenges that increase the learning cost: (1) how to evaluate intelligent algorithms in optical network for data center rapidly and automatically, (2) how to provide a large-scale optical network for data center environment for students’ practice with acceptable cost. To overcome these two challenges, this paper proposed an innovative educational platform with two features: (1) Introducing an intelligent algorithm center in the control layer to store and manage students’ different customized intelligent algorithms. (2) Introducing the combination of physical domain and virtual domain in underlying devices layer to provide a large-scale network experimental environment for students. The main functions of the proposed platform have been realized. Many students have used this platform to evaluate their intelligent algorithms. The difficulty of evaluating intelligent algorithms is greatly reduced. Students can make it more clear how intelligent algorithm works on optical networks for data center.

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