Presentation Information

[TuG1-2]Level-aware Service Degradation in Resource-time Dimension for Resource-intensive Services in Computing Power Network

○Yingbo Fan1, Yajie Li1,2, Yahui Wang1, Wanping Wu1, Wei Wang1, Yongli Zhao1, Jie Zhang1 (1. Beijing University of Posts and Telecommunications (China), 2. School of Information Science and Technology, Tibet University (China))

Keywords:

Data center,in-building/in-home,local area,and storage area optical networks,Artificial intelligence and machine learning for optical network design,control,and management,End-to-end all photonics network; architecture,system design and enabling technologies

This paper proposes an ILP model and level-aware degradation algorithm for resource-intensive services in CPN, degrading in resource-time dimension and emphasizing computing and bandwidth relationships to improve network revenue and reduce blocking probability by 20%.

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