User-side flexible resource scheduling method based on differential expansion and differential translation

Jian Liu; Boyu Zhou; Min You; Yu Bai; Yilei Gu; Yunpeng Jiang

doi:10.1117/12.3050033

8 November 2024 User-side flexible resource scheduling method based on differential expansion and differential translation

Jian Liu, Boyu Zhou, Min You, Yu Bai, Yilei Gu, Yunpeng Jiang

Author Affiliations +

Proceedings Volume 13416, Fourth International Conference on Advanced Algorithms and Neural Networks (AANN 2024); 1341622 (2024) https://doi.org/10.1117/12.3050033
Event: 2024 4th International Conference on Advanced Algorithms and Neural Networks, 2024, Qingdao, China

Abstract

In order to meet the diverse needs of user-side flexible resources and ensure interconnection, a flexible resource scheduling method based on differential expansion and differential translation is proposed. Analyze the reliability of information sources, obtain the confidence interval of resource scheduling, select the cluster head node, ensure the optimal position of other nodes in the same cluster, and extract the flexible resource characteristics of the user side; Designing a resource allocation mode, and according to the mode, constructing a flexible resource allocation index on the user side; The flexible resource scheduling steps of user side are analyzed under differential expansion and differential translation respectively. The experimental results show that the throughput of this method is always above 0.9Mbps, and the highest resource utilization rate is 99.65%, which can realize load optimization and better scheduling.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Jian Liu, Boyu Zhou, Min You, Yu Bai, Yilei Gu, and Yunpeng Jiang "User-side flexible resource scheduling method based on differential expansion and differential translation", Proc. SPIE 13416, Fourth International Conference on Advanced Algorithms and Neural Networks (AANN 2024), 1341622 (8 November 2024); https://doi.org/10.1117/12.3050033

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