The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Aug. 12, 2025

Filed:

Jan. 18, 2025
Applicants:

Shandong Computer Science Center (National Supercomputer Center IN Jinan), Shandong, CN;

Qilu University of Technology (Shandong Academy of Sciences), Shandong, CN;

Inventors:

Yinglong Wang, Jinan, CN;

Jing Chen, Jinan, CN;

Meihong Yang, Jinan, CN;

Ying Guo, Jinan, CN;

Xiaoming Wu, Jinan, CN;

Jing Ge, Jinan, CN;

Na Li, Jinan, CN;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
H04L 67/1097 (2022.01); H04L 67/101 (2022.01); H04L 67/1012 (2022.01);
U.S. Cl.
CPC ...
H04L 67/1097 (2013.01); H04L 67/101 (2013.01); H04L 67/1012 (2013.01);
Abstract

Method for computing power network scheduling service based on comprehensive weight decision of network performance and the system thereof are provided. A computing power network service platform combines the filtered storage platforms and at least one filtered computing power platform that do not belong to a same data center to obtain a plurality of combinations; constructs a multi-objective optimization function under a storage-computing separation scenario based on the different network performance indicators, subjective weight vectors of the different network performance indicators, objective weight vectors of the different network performance indicators between the storage platforms and the computing power platforms for each combination, and resource demand of the user, and solves the multi-objective optimization function to obtain the optimal combination of the storage platform and the computing power platform that meets an user demand; and deploys job and computational data of the user to the optimal combination for storage and computation.


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