Huawei Technologies Co., Limited

Dewei Bao

Qikun Wei

Xiaofei Bai

Zhenhang Sun

Fuqing Sun

Shihao Li

Liang Zhang

Zhiqiang Li

Lv Ding

Jian Tong Li

Jun Wu

Li Xue

Yaodong Guan

Yuming Xie

Haonan Ye

Donghong Peng

Xiaoyun Si

Yunpeng Gao

Zhongyu Wang

Jiyuan Shi

Tao Feng

Zhi Ma

Juzheng Yu

Sheng Jin

Zhiman Xiong

Qiaoling Wang

Liang Tao

Zhiping Xu

Changlu Li

Jian Li

Embodiments of this application disclose a group-based calibration method and device. The method includes: A control device that obtains path loss data of a wireless access point AP set, where the AP set includes a plurality of APs, and the path loss data includes a path loss between any two of the plurality of APs. The control device obtains a first calibration group based on the path loss data, and sends first calibration information to a management AP of the first calibration group, where the management AP of the first calibration group is an AP that performs calibration management in the first calibration group. By implementing the foregoing method, the control device may divide a plurality of APs into a plurality of calibration groups based on path loss data between the APs, to decrease a coupling degree between the calibration groups.

Wireless access point group-based calibration method and device, and computer storage medium

A detection method includes: obtaining at least one feature of a first access point (AP), where the at least one feature includes a quantity of target terminals that request to access the first AP within a time period with duration being first duration, and the target terminal is a terminal whose access status is abnormal; and detecting, based on the at least one feature, whether the first AP is a logical edge AP, where the logical edge AP is an AP whose signal coverage area reaches an edge of a signal coverage area of a wireless local area network (WLAN) in which the AP is located.

Detection method, apparatus, and system

Embodiments of this application disclose an interference source detection method, apparatus, device, and system, and a storage medium. The method includes: obtaining data detected by a plurality of access points (Aps), where data detected by any AP of the plurality of APs includes load information and radio frequency information of the any AP, received signal strength indicator RSSI information between the any AP and a neighbor of the any AP, and load information and radio frequency information of the neighbor of the any AP; determining a global neighbor topology based on the data detected by the plurality of APs; and determining an interference source based on the global neighbor topology.

Interference source detection method, apparatus, device, and system, and storage medium

Embodiments of this application disclose a radio frequency resource allocation method, apparatus, device, system, and a storage medium. The method includes: obtaining radio frequency information of an access point AP (for example, RSSI signal strength between the AP and each neighboring AP, and data traffic of the AP in a data collection period), predicting, based on the radio frequency information of the AP, load of the AP that is in target duration after a current moment, and allocating a radio frequency resource to the AP based on the load of the AP. This implementation can reduce actual interference on an entire network and improve user experience.

Radio frequency resource allocation method, apparatus, device and system, and storage medium

A fault root cause identification method, apparatus, and device. For a failure flow that occurs when a connectivity fault for access in a network occurs, a target success flow that has a high similarity with the failure flow is determined from a plurality of success flows in the network based on the failure flow. Then, a target fault root cause of the failure flow is obtained based on the failure flow, the target success flow, and a trained first machine learning model. In this way, the target success flow related to the failure flow is determined from the plurality of success flows in the network, and the first machine learning model trained by using a large quantity of success flows and failure flows whose feature indicators are slightly different from each other is used.

Fault root cause identification method, apparatus, and device

In a forwarding fault location determining method, a controller receives a plurality of table search statistical results of a plurality of forwarding tables for a first service from one or more forwarders. The plurality of forwarding tables include a first forwarding table and a second forwarding table, and the first forwarding table is prior to the second forwarding table in terms of a search sequence. Subsequently, the controller determines that table search behavior of the first forwarding table for the first service is normal and table search behavior of the second forwarding table for the first service is abnormal. The controller determines, based on the determining result, that the second forwarding table is a faulty forwarding table for the first service.

Forwarding fault location determining method and device

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.

Network quality monitoring method and apparatus

A network log time alignment method and an apparatus are provided. The method includes: obtaining log data stored in multiple network devices; parsing the log data to obtain features of each network device; determining associated features of the multiple network devices according to the features of each network device, where the associated features are features that are of the network devices and that have an association in space; and then, performing alignment on log time in multiple pieces of log data according to the associated features. Therefore, associated features of related devices of a network fault can be found, and log time are automatically aligned according to the associated features, thereby improving the efficiency and the accuracy of the fault location and sectionalization.

Network log time alignment method, apparatus, and host

In a terminal roaming steering method, a steering protocol supported by a terminal and a second AP are determined, and the terminal is steered, based on the steering protocol supported by the terminal, to roam from a first AP to the second AP.

Terminal roaming steering method and devices, and computer-readable storage medium

An alarm log compression method, apparatus, system, and a storage medium are provided. The method includes: obtaining a historical alarm log set generated by a first network device; dividing the historical alarm log set into a plurality of historical alarm log subsets based on a generation time stamp of a historical alarm log in the historical alarm log set, where all historical alarm logs in each historical alarm log subset are consecutive in a time sequence; determining a correspondence between an alarm type in the historical alarm log set and the plurality of historical alarm log subsets; performing clustering processing on the alarm types in the historical alarm log set based on the correspondence, to generate at least one association rule; and compressing to-be-processed alarm logs based on the at least one association rule, to obtain an alarm log whose alarm type is a root cause alarm type.

Alarm log compression method, apparatus, and system, and storage medium

A method and an apparatus for locating a fault cause are provided. The method includes: obtaining parameter values of a plurality of running parameters and a parameter value of a fault parameter in preset duration before a wavelength division multiplexing board device is faulty; determining a correlation between each of the plurality of running parameters and the fault parameter; and determining at least one target parameter from the plurality of running parameters based on a value of the correlation, where a correlation between each of the at least one target parameter and the fault parameter is greater than a correlation between the fault parameter and a running parameter other than the at least one target parameter in the plurality of running parameters. Accuracy of locating a fault cause can be improved in the embodiments of the present disclosure.

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Nanjing, China

Dewei Bao