| US 11,792,137 B2 | ||
| Dynamic network resource allocation method based on network slicing | ||
| Gang Sun, Chengdu (CN); Qing Li, Chengdu (CN); Yuhui Wang, Chengdu (CN); Hongfang Yu, Chengdu (CN); Jian Sun, Chengdu (CN); and Jing Ren, Chengdu (CN) | ||
| Assigned to UNIVERSITY OF ELECTRONIC SCIENCE AND TECHNOLOGY OF CHINA, Chengdu (CN) | ||
| Filed by UNIVERSITY OF ELECTRONIC SCIENCE AND TECHNOLOGY OF CHINA, Chengdu (CN) | ||
| Filed on Jul. 27, 2022, as Appl. No. 17/874,313. | ||
| Claims priority of application No. 202111004167.1 (CN), filed on Aug. 30, 2021. | ||
| Prior Publication US 2023/0062221 A1, Mar. 2, 2023 | ||
| Int. Cl. H04L 41/147 (2022.01); H04L 47/83 (2022.01) | ||
| CPC H04L 47/83 (2022.05) [H04L 41/147 (2013.01)] | 7 Claims |
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1. A dynamic network resource allocation method based on network slicing, comprising:
S1: inputting a historical resource demand dataset of an accessed network slice into a first neural network for training; S2: determining, based on a trained first neural network and the historical resource demand of the accessed network slice, resource demand prediction information corresponding to the accessed network slice in a first prediction time period; and S3: pre-allocating resources to the accessed network slice based on the resource demand prediction information, and allocating resources to the accessed network slice when the first prediction time period arrives; wherein the resource demand prediction information comprises a predicted node resource quantity and a predicted link resource quantity; wherein the step of pre-allocating resources to the accessed network slice in the step S3 comprises determining a pre-allocated node resource quantity and a pre-allocated link resource quantity of the accessed network slice in the first prediction time period according to the following formulas:
 wherein if
  wherein
 is a pre-allocated node resource quantity of an accessed network slice i in a first prediction time period t,
 is a pre-allocated link resource quantity of the accessed network slice i in the first prediction time period t,
 is a predicted node resource quantity of the accessed network slice i in the first prediction time period t,
 is a predicted link resource quantity of the accessed network slice i in the first prediction time period t, n
t is a quantity of accessed network slices in a system in the first prediction time period t, γd ≥ 1 represents node resource redundancy, γl ≥ 1 represents link resource redundancy,
 and
 are offsets of corresponding predicted values, D is a total node resource quantity of the system, and L is a total link resource quantity of the system.
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