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公开(公告)号：US20210006481A1
公开(公告)日：2021-01-07
申请号：US17027319
申请日：2020-09-21
Applicant: Huawei Technologies Co., Ltd.
Inventor： Yunpeng Gao , Yuming Xie , Xin Xiao , Liang Zhang
Abstract: A method and an apparatus for determining a status of a network device are provided. A warning analysis device obtains a plurality of pieces of target key performance indicator KPI data of the network device within preset duration, processes the plurality of pieces of target KPI data to generate an element, forms the feature vector by using generated elements corresponding to the plurality of pieces of feature information, and analyzes the feature vector based on a preset warning analysis model, to determine the status of the network device. In this way, the status of the network device is determined by analyzing a plurality of pieces of target KPI data within a period of time, instead of by using only data at a moment. This improves the accuracy of determining the network device, so as to reduce an omission of a warning.
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公开(公告)号：US20200092302A1
公开(公告)日：2020-03-19
申请号：US16692616
申请日：2019-11-22
Applicant: Huawei Technologies Co., Ltd.
Inventor： Qian Xiao , Yuming Xie , Jun Wu , Liang Zhang
Abstract: A data packet sending method, a network device, a control device, and a network system includes receiving a first data packet sent by a first device, where a packet header of the first data packet includes a first sequence number marker sequence, a first position marker sequence, a first accumulated value, and a verification value; obtaining a second data packet, where a packet header of the second data packet includes a second sequence number marker sequence, a second position marker sequence, a second accumulated value, and the verification value; and sending the second data packet to a second device.
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公开(公告)号：US20180268115A1
公开(公告)日：2018-09-20
申请号：US15923703
申请日：2018-03-16
Applicant: Huawei Technologies Co., Ltd.
Inventor： Liang Zhang , Jianrui Yang , Xingshui Dong
IPC: G06F21/10
CPC classification number: G06F21/105 , G06F8/63 , G06F9/445 , G06F9/455 , G06F21/121 , G06F2221/0768
Abstract: A container license management method and an apparatus, where the method includes receiving an image download request including information for requesting a license from a container management background, obtaining an image according to the image download request, obtaining the information for requesting a license in the image download request, generating a license image layer corresponding to the information for requesting a license, adding the license image layer to the obtained image, and sending, to the container management background, the image to which the license image layer is added such that the container management background starts a container corresponding to the image, and detects whether the license image layer is valid. Hence, container license management efficiency can be improved.
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14.发明申请公开(公告)号：US20170039089A1
公开(公告)日：2017-02-09
申请号：US15277926
申请日：2016-09-27
Applicant: Huawei Technologies Co., Ltd.
Inventor： Jinwei Xia , Xinyu Hu , Liang Zhang
CPC classification number: G06F9/5005 , G06F9/455 , G06F9/4555 , G06F9/5044 , G06F9/544 , G06F2009/45595
Abstract: The present invention discloses a method and an apparatus for implementing acceleration processing on a VNF. In the present invention, an acceleration request of performing acceleration processing on a virtualized network function VNF is received; a hardware acceleration device capable of performing acceleration processing on the VNF is determined according to the acceleration request; and an acceleration resource of the hardware acceleration device is allocated to the VNF, so as to perform acceleration processing on the VNF. According to the present invention, a corresponding hardware acceleration device can be dynamically selected for and allocated to a VNF, implementing virtualized management on the hardware acceleration device, and improving resource utilization.
Abstract translation: 本发明公开了一种用于在VNF上实现加速处理的方法和装置。 在本发明中，接收对虚拟化网络功能VNF执行加速处理的加速请求; 根据加速要求确定能够对VNF进行加速处理的硬件加速装置; 将硬件加速装置的加速资源分配给VNF，对VNF进行加速处理。 根据本发明，可以动态地选择对应的硬件加速装置并分配给VNF，在硬件加速装置上实现虚拟化管理，提高资源利用率。
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公开(公告)号：US12294525B2
公开(公告)日：2025-05-06
申请号：US17896943
申请日：2022-08-26
Applicant: Huawei Technologies Co., Ltd.
Inventor： Jun Wu , Xinyu Hu , Liang Zhang , Huiying Xu
IPC: H04L47/2441 , G06N20/00 , H04L41/14 , H04L41/147 , H04L47/2483
Abstract: A data stream classification model updating method is disclosed. Determining, based on packet information of a current data stream and a behavior classification model, a first data stream class corresponding to the current data stream; determining, based on a target correspondence and a common feature of the current data stream, a second data stream class corresponding to the current data stream, where the target correspondence is a correspondence between a plurality of common features and a plurality of data stream classes; and if the first data stream class is different from the second data stream class, obtaining correction data corresponding to the current data stream, where the correction data includes the packet information of the current data stream and the second data stream class, and the correction data is used as a training sample to update the behavior classification model.
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Patent Agency Ranking
公开(公告)号：US12107766B2
公开(公告)日：2024-10-01
申请号：US17695540
申请日：2022-03-15
Applicant: Huawei Technologies Co., Ltd.
Inventor： Haonan Ye , Huafeng Wen , Liang Zhang , Ke Meng
IPC: H04L47/11 , H04L41/14 , H04L43/062 , H04L47/127
CPC classification number: H04L47/11 , H04L41/145 , H04L43/062 , H04L47/127
Abstract: A network congestion handling method includes obtaining network status information; determining, based on the network status information and an Explicit Congestion Notification (ECN) optimization model, a reference probability corresponding to recommended ECN configuration information; determining destination ECN configuration information based on the reference probability; and performing ECN marking on a packet by using the destination ECN configuration information.
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公开(公告)号：US12101238B2
公开(公告)日：2024-09-24
申请号：US16730465
申请日：2019-12-30
Applicant: Huawei Technologies Co., Ltd.
Inventor： Jian Cheng , Yanfang Zhang , Yan Bai , Liang Zhang
IPC: H04L43/08 , H04L1/08 , H04L5/00 , H04L69/22 , H04L69/326
CPC classification number: H04L43/08 , H04L1/08 , H04L5/0055 , H04L69/22 , H04L69/326
Abstract: A method for implementing transmission performance detection includes: after successively receiving data packets whose sequence numbers are N1 and N2, determining, by a detection apparatus, that N2 is greater than N1 and that N1 and N2 are inconsecutive; after receiving the data packet whose sequence number is N2, receiving a data packet whose sequence number is M1; and when determining N1 =RTT, determining that the data packet whose sequence number is M1 is a retransmitted packet corresponding to an upstream packet loss, where T1 is a time for receiving the data packet whose sequence number is N2, T2 is a time for receiving the data packet whose sequence number is M1.
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公开(公告)号：US11956118B2
公开(公告)日：2024-04-09
申请号：US17342659
申请日：2021-06-09
Applicant: HUAWEI TECHNOLOGIES CO., LTD.
Inventor： Xiaoyun Si , Dewei Bao , Liang Zhang , Zhenhang Sun
IPC: H04L41/0654 , H04L41/0631 , H04L41/16
CPC classification number: H04L41/065 , H04L41/0654 , H04L41/16
Abstract: 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.
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公开(公告)号：US11706079B2
公开(公告)日：2023-07-18
申请号：US17184772
申请日：2021-02-25
Applicant: HUAWEI TECHNOLOGIES CO., LTD.
Inventor： Yuming Xie , Liang Zhang , Wei Song , Lei Zhang
IPC: H04L12/24 , H04L41/0631 , H04L41/0604 , H04L41/0654 , H04L41/12
CPC classification number: H04L41/0631 , H04L41/0627 , H04L41/0654 , H04L41/12
Abstract: A fault recovery method and apparatus, and a storage medium are provided, and belong to the field of Internet technologies. In the method, network composition information and abnormal event information of a target network are obtained, where the network composition information includes a network topology of the target network and device information of a plurality of network devices on the target network, and the device information includes one or more of interface configuration information, protocol configuration information, and service configuration information; and then a possible root cause of a fault of the target network is determined based on the network composition information and the abnormal event information, where the possible root cause of the fault is used to determine a corresponding fault recovery plan.
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20.发明申请公开(公告)号：US20230031387A1
公开(公告)日：2023-02-02
申请号：US17957889
申请日：2022-09-30
Applicant: HUAWEI TECHNOLOGIES CO., LTD.
Inventor： Xiaoyun Si , Xinyu Hu , Li Xue , Liang Zhang , Fuxing Chen
Abstract: A method, an apparatus, and a device for obtaining an artificial intelligence model, and a storage medium are provided. A client receives a first artificial intelligence AI model sent by a service end (303). The first AI model includes a plurality of neurons. The client determines, from the plurality of neurons, a target neuron participating in a current round of training, where the current round of training is a non-first round of training, and a quantity of target neurons is less than a total quantity of the plurality of neurons (304). The client trains the target neuron based on local data (305). The client returns parameter data corresponding to the target neuron to the service end (306). The parameter data corresponding to the target neuron is used by the service end to obtain a converged target AI model.
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