Presentation Information

9:45 AM - 10:00 AM JST(12:45 AM - 1:00 AM UTC)

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

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

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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