公开(公告)号：US20200267063A1

公开(公告)日：2020-08-20

申请号：US16868699

申请日：2020-05-07

Applicant: HUAWEI TECHNOLOGIES CO., LTD.

Inventor： Haonan YE ,  Liang ZHANG ,  Jian CHENG ,  Jun WU ,  Li XUE

IPC: H04L12/26 ,  H04L29/06 ,  H04L12/24

Abstract: A sampling frequency recommendation method, apparatus, and device, and a storage medium relating to the field of communications technologies are disclosed. The sampling frequency recommendation method includes: obtaining a network key performance indicator of a to-be-analyzed data stream; sampling the network key performance indicator based on a plurality of different sampling frequencies to obtain an experience quality sequence corresponding to each sampling frequency, where the plurality of different sampling frequencies include one standard sampling frequency and at least two to-be-tested sampling frequencies, and the standard sampling frequency is greater than each to-be-tested sampling frequency; and determining a matching degree between an experience quality sequence corresponding to each to-be-tested sampling frequency and a standard experience quality sequence, and determining a recommended sampling frequency based on the matching degree between the experience quality sequence corresponding to each to-be-tested sampling frequency and the standard experience quality sequence.

公开(公告)号：US20230394373A1

公开(公告)日：2023-12-07

申请号：US18454868

申请日：2023-08-24

Applicant: HUAWEI TECHNOLOGIES CO., LTD.

Inventor： Haonan YE ,  Weiwang XU ,  Li XUE ,  Jian CHENG

IPC: G06N20/00

CPC classification number: G06N20/00

Abstract: The technology of this disclosure relates to a method, an apparatus, a device, a storage medium, and a system for determining a collection period. The technology relates to the field of machine learning technologies. In this disclosure, a machine learning model is obtained by using a training dataset collected based on candidate collection periods of X features, and a candidate collection period of each of the X features is determined as a target collection period of each feature based on the obtained machine learning model and a first condition. Because the target collection period of each feature is greater than a minimum collection period of each feature, subsequently, if data is collected based on the target collection period of each feature, an amount of the collected data is reduced, to reduce collection load of a device and memory occupied by sampled data, thereby reducing time redundancy.

公开(公告)号：US20220210071A1

公开(公告)日：2022-06-30

申请号：US17696643

申请日：2022-03-16

Applicant: HUAWEI TECHNOLOGIES CO., LTD.

Inventor： Ke MENG ,  Hewen ZHENG ,  Haonan YE ,  Weiqing KONG

IPC: H04L47/122 ,  H04L47/125 ,  H04L47/70 ,  H04L47/10 ,  H04L41/12

Abstract: A network congestion control method, a node and a system are disclosed, where the method is applied to a spine-leaf network system. The method includes: a spine node receives network information sent by the at least one leaf node, where the network information includes network topology information of the leaf node and a network performance indicator of the leaf node; networks the at least one leaf node and the spine node based on the network topology information of the at least one leaf node, to obtain a combined network topology; and if the combined network topology is a global network topology of the spine-leaf network system, performs network congestion control on the at least one leaf node based on the network performance indicator of the at least one leaf node.

公开(公告)号：US20210274369A1

公开(公告)日：2021-09-02

申请号：US17325933

申请日：2021-05-20

Applicant: HUAWEI TECHNOLOGIES CO., LTD.

Inventor： Jun WU ,  Dewei BAO ,  Lv DING ,  Zhenhang SUN ,  Haonan YE

IPC: H04W24/08

Abstract: This application provides a network quality monitoring method and apparatus. A network quality monitoring apparatus obtains network running data, where the network running data includes dynamic data corresponding to a plurality of sampling periods and static data that are of an AP; determines one channel efficiency value of the AP based on each of a plurality of groups of dynamic data of the AP, so as to obtain a plurality of channel efficiency values of the AP; determines a channel efficiency baseline of the AP based on the static data of the AP; and determines, based on the plurality of channel efficiency values of the AP and the channel efficiency baseline of the AP, network quality of a wireless local area network in which the AP is located.