Huawei Technologies Co., Limited

Qingping Yang

Wei Song

Feng Dong

Chuntao Wang

Hanshu Hong

Fangfang Yu

Wanyu Li

Linjie Huang

Jiaming Tian

Embodiments of this application disclose a method and an apparatus for generating an application identification model. The method includes: obtaining Y data packets, where the Y data packets correspond to P applications, an iapplication in the P applications corresponds to M(i) data packets, and Y=ΣM(i), 1≤i≤P; extracting a target parameter of each of the M(i) data packets of each of the P applications to obtain M(i) samples, where the target parameter indicates information about a session connection established between the iapplication and a server that provides the iapplication; and training an initial identification model based on the M(i) samples of each of the P applications, to obtain a first application identification model, where the first application identification model is used to determine, based on a target parameter of a data packet, an application corresponding to the data packet.

Method and apparatus for generating application identification model

A poor-QoE assessment method and a related device are provided. The method includes: obtaining m data streams transmitted by a network device; screening the m data streams, and determining that p data streams in the m data streams and that meet a first preset condition are data streams corresponding to a first type; performing feature extraction on the data streams corresponding to the first type, to obtain known feature vectors corresponding to the first type; training, by using the known feature vectors corresponding to the first type, an untrained first poor-QoE assessment model, to obtain a trained first poor-QoE assessment model; and performing, by using the trained first poor-QoE assessment model, poor-QoE assessment on n data streams corresponding to the first type, to obtain a first poor-QoE assessment result. This method can be universally used instead of an application.

Poor-QoE assessment method and related device

Embodiments of this application disclose a service type determining method and a related device. A first device obtains a dataset, where the dataset includes at least two 5-tuples. The first device determines a target feature (the target feature is used to indicate a service type corresponding to a target triplet) corresponding to the target triplet based on the dataset. In this way, the first device can identify the service type corresponding to the target triplet based on the target feature, to facilitate operations such as packet transmission traffic control or application identification based on the importance indicated by the service type.

Service type determining method and related device

A method and an apparatus for predicting a fault of an optical circuit includes determining a classification threshold of an operating parameter based on a classification sample set corresponding to the operating parameter of optical circuit and predicting, based on comparison results between the classification threshold and a plurality of measured values in a sequence, whether a fault occurs in the future on the optical circuit corresponding to the sequence.

Method, apparatus and device for predicting fault of optical module

In a video quality assessment method, an assessment model is first generated based on a subjective assessment result of a user on each sample in a sample set and based on a parameter set (a parameter type in the parameter set may include at least one of a packet loss rate, a delay, and a jitter) of each sample. Therefore, when video quality is being assessed, a parameter set of a to-be-assessed video is obtained first, where the parameter set of the to-be-assessed video has a same parameter type as the parameter set of each sample that is used to generate the assessment model; and then video quality of the to-be-assessed video is assessed based on the assessment model and the parameter set of the to-be-assessed video, to obtain an assessment result.

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Nanjing, China

Qingping Yang