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公开(公告)号：US09768801B1
公开(公告)日：2017-09-19
申请号：US15597963
申请日：2017-05-17
Applicant: HUAWEI TECHNOLOGIES CO., LTD.
Inventor： Zhenguo Li , Ge Luo , Ke Yi , Wei Fan , Cheng He
IPC: H03M7/30
CPC classification number: H03M7/30 , H03M7/3064
Abstract: A method for compressing flow data, including: constructing multiple line segments according to flow data and a predefined maximum error that are acquired; obtaining a target piecewise linear function according to the multiple line segments, where the target piecewise linear function includes multiple linear functions, and an intersection set of value ranges of independent variables of every two linear functions among the multiple linear functions includes a maximum of one value; and outputting a reference data point according to the target piecewise linear function, where the reference data point includes a point of continuity and a point of discontinuity of the target piecewise linear function. In this way, a maximum error, a target piecewise linear function is further determined according to the multiple line segments, and a point of continuity and a point of discontinuity of the target piecewise linear function are used to represent compressed flow data.
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公开(公告)号：US10218381B2
公开(公告)日：2019-02-26
申请号：US15697066
申请日：2017-09-06
Applicant: HUAWEI TECHNOLOGIES CO., LTD.
Inventor： Zhenguo Li , Ge Luo , Ke Yi , Wei Fan , Cheng He
IPC: H03M7/30
Abstract: A method for compressing flow data, including: generating multiple line segments according to flow data and a predefined maximum error that are acquired; obtaining a target piecewise linear function according to the multiple line segments, where the target piecewise linear function includes multiple linear functions, and an intersection set of value ranges of independent variables of every two linear functions among the multiple linear functions includes a maximum of one value; and outputting a reference data point according to the target piecewise linear function, where the reference data point includes a point of continuity and a point of discontinuity of the target piecewise linear function. In this way, a maximum error, a target piecewise linear function is further determined according to the multiple line segments, and a point of continuity and a point of discontinuity of the target piecewise linear function are used to represent compressed flow data.
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3.发明申请公开(公告)号：US20180367584A1
公开(公告)日：2018-12-20
申请号：US16112236
申请日：2018-08-24
Applicant: HUAWEI TECHNOLOGIES CO.,LTD.
Inventor： Yunlong Shi , Mingzhen Xia , Cheng He
IPC: H04L29/06 , G06F9/50 , H04L12/911 , H04L12/26
Abstract: A stream computer system and a method for processing a data stream in a stream computing system are disclosed. The method includes a first working node invokes at least one execution unit to process a data stream according to an initial parallelism degree, a control node collects information reflecting data traffic between the first working node and a second working node, and information reflecting data processing speed of the first working node, determines an optimized parallelism degree for the first working node according to the collected information, and adjusts the parallelism degree of the first working node to be consistent with the optimized parallelism degree.
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4.发明授权公开(公告)号：US10097595B2
公开(公告)日：2018-10-09
申请号：US15257722
申请日：2016-09-06
Applicant: Huawei Technologies Co., Ltd.
Inventor： Yunlong Shi , Mingzhen Xia , Cheng He
IPC: H04L29/06 , G06F9/50 , H04L12/26 , H04L12/911
Abstract: A stream computer system and a method for processing a data stream in a stream computing system are disclosed. In an embodiment, the method includes collecting data traffic information between each working node and other working nodes and processing speed information for each working node, determining an optimized parallelism degree for each working node according to the collected data traffic information and processing speed information and adjusting a parallelism degree of the working node according to the optimized parallelism degree of the working node.
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公开(公告)号：US09740816B2
公开(公告)日：2017-08-22
申请号：US13953486
申请日：2013-07-29
Applicant: Huawei Technologies Co., Ltd.
CPC classification number: G06F17/509 , G06F11/3447 , G06F11/3457 , H04L41/145 , H04L43/08 , H04L63/1408
Abstract: Embodiments of the present invention provide a method and an apparatus for network traffic simulation. The method includes: obtaining traffic information and user requirement information of a to-be-simulated IP network; analyzing the traffic information to generate a traffic characteristic; according to correspondence between user requirement information and traffic models, obtaining a traffic model corresponding to the user requirement information; and generating, through simulation, traffic of the to-be-simulated IP network according to the traffic characteristic and the traffic model. The embodiments of the present invention can improve flexibility and an emulation degree of traffic simulation.
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Patent Agency Ranking
公开(公告)号：US20170046387A1
公开(公告)日：2017-02-16
申请号：US15339530
申请日：2016-10-31
Applicant: Huawei Technologies Co., Ltd.
Inventor： Jiefeng Cheng , Cheng He , Wei Fan
IPC: G06F17/30
CPC classification number: G06F16/24542 , G06F16/2455 , G06F16/9024
Abstract: The present invention discloses a method and apparatus for querying a nondeterministic graph, which are used to implement quick query of a nondeterministic graph, reduce query complexity, and improve query efficiency. The method comprises receiving a query instruction, where the query instruction is used to query a nondeterministic graph for data that satisfies a query condition; determining two vertices in the nondeterministic graph according to the query instruction; determining all possible paths that use one vertex in the two vertices as a start point and the other vertex as an end point; calculate a probability of a first event or a second event corresponding to each of the paths; and obtaining, according to the probability of the first event or the probability of the second event, a query result corresponding to the query instruction.
Abstract translation: 本发明公开了一种查询非确定性图的方法和装置，用于实现非确定性图形的快速查询，减少查询复杂度，提高查询效率。 该方法包括接收查询指令，其中使用查询指令来查询满足查询条件的数据的非确定性图; 根据查询指令确定非确定性图中的两个顶点; 确定使用两个顶点中的一个顶点作为起始点和另一个顶点作为终点的所有可能路径; 计算与每个路径相对应的第一事件或第二事件的概率; 并且根据第一事件的概率或第二事件的概率获得与查询指令相对应的查询结果。
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7.发明申请公开(公告)号：US20150319069A1
公开(公告)日：2015-11-05
申请号：US14798811
申请日：2015-07-14
Applicant: Huawei Technologies Co., Ltd.
Inventor： Cheng He , Qun Huang , Pak-Ching Lee
IPC: H04L12/26
CPC classification number: H04L43/0882 , H04L43/026 , H04L43/0888 , H04L43/0894 , H04L63/1441
Abstract: A method, an apparatus, and a system for identifying an abnormal IP data stream, which are used to improve identification accuracy. The method provided by the embodiments of the present invention includes: receiving Y elements sent by a data collection node; mapping the Y elements to N buckets; acquiring a bucket in the N buckets as a target bucket; acquiring r upper traffic limits of a first object in r buckets within the current time interval, the first object is any object mapped to the target bucket; and identifying, according to a preset abnormal object type and the r upper traffic limits within the current time interval, whether the first object is an abnormal object, where the preset abnormal object type is a heavy hitter or a heavy changer.
Abstract translation: 用于识别异常IP数据流的方法，装置和系统，其用于提高识别精度。 本发明实施例提供的方法包括：接收由数据收集节点发送的Y个元素; 将Y元素映射到N个桶; 在N个桶中获取桶作为目标桶; 在当前时间间隔内获取r个桶中第一个对象的上限流量限制，第一个对象是映射到目标桶的任何对象; 根据预设的异常对象类型和当前时间间隔内的上游流量限制来识别第一对象是异常对象，其中预设的异常对象类型是重型打击机还是重型更换器。
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公开(公告)号：US20190171367A1
公开(公告)日：2019-06-06
申请号：US16259138
申请日：2019-01-28
Applicant: HUAWEI TECHNOLOGIES CO.,LTD.
Inventor： Cheng He , Qun Huang , Pak-Ching Lee
IPC: G06F3/06
Abstract: In a data processing method, a worker node in a distributed data processing system receives first data from an upstream worker node. The first data has been stored in a buffer of the upstream worker node. The worker node sends a first portion of the first data to a persistent storage device of the distributed data processing system for persistent backup, and performs computational processing on the first data to generate second data. Prior to completing performing computational processing on the first data, the worker node sends acknowledgement information to the upstream worker node to instruct the upstream node to delete the first data from the buffer of the upstream worker node. The worker node then sends the second data to a downstream worker node in the distributed data processing system for further processing by the downstream worker node.
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公开(公告)号：US10296827B2
公开(公告)日：2019-05-21
申请号：US14944294
申请日：2015-11-18
Applicant: Huawei Technologies Co., Ltd.
Inventor： Guangjian Tian , Cheng He , Wei Fan
Abstract: A deep neural network to which data category information is added is established locally, to-be-identified data is input to an input layer of the deep neural network generated based on the foregoing data category information, and information of a category to which the to-be-identified data belongs is acquired, where the information of the category is output by an output layer of the deep neural network. A deep neural network is established based on data category information, such that category information of to-be-identified data is conveniently and rapidly obtained using the deep neural network, thereby implementing a category identification function of the deep neural network, and facilitating discovery of an underlying law of the to-be-identified data according to the category information of the to-be-identified data.
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公开(公告)号：US20170250705A1
公开(公告)日：2017-08-31
申请号：US15597963
申请日：2017-05-17
Applicant: HUAWEI TECHNOLOGIES CO.,LTD.
Inventor： Zhenguo Li , Ge Luo , Ke Yi , Wei Fan , Cheng He
IPC: H03M7/30
CPC classification number: H03M7/30 , H03M7/3064
Abstract: A method for compressing flow data, including: constructing multiple line segments according to flow data and a predefined maximum error that are acquired; obtaining a target piecewise linear function according to the multiple line segments, where the target piecewise linear function includes multiple linear functions, and an intersection set of value ranges of independent variables of every two linear functions among the multiple linear functions includes a maximum of one value; and outputting a reference data point according to the target piecewise linear function, where the reference data point includes a point of continuity and a point of discontinuity of the target piecewise linear function. In this way, a maximum error, a target piecewise linear function is further determined according to the multiple line segments, and a point of continuity and a point of discontinuity of the target piecewise linear function are used to represent compressed flow data.
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