公开(公告)号：US10686672B2

公开(公告)日：2020-06-16

申请号：US16226577

申请日：2018-12-19

Applicant: HUAWEI TECHNOLOGIES CO., LTD.

Inventor： Trimponias Georgios ,  Zhitang Chen ,  Yanhui Geng

IPC: G06F15/16 ,  H04L12/24 ,  G06N3/04 ,  G06N3/08 ,  H04L12/715 ,  H04L12/751 ,  H04L12/26 ,  H04L12/761

Abstract: Embodiments of this application provide a method for generating a routing control action in a software-defined network and a related device, to provide optimum control actions for the SDN. The method includes: obtaining a current network state parameter of the SDN; determining a Q function of the SDN based on the current network state parameter of the SDN and a deep neural network model, where the deep neural network model is determined based on a current topology structure of the SDN; and determining a routing control action for the SDN based on the Q function and a link state parameter of each link in the SDN. In the technical solution, the deep neural network model is combined with a Q-learning algorithm of reinforcement learning, and optimum control actions can be determined.

公开(公告)号：US10333854B2

公开(公告)日：2019-06-25

申请号：US15465757

申请日：2017-03-22

Applicant: Huawei Technologies Co., Ltd.

Inventor： Zhitang Chen ,  Yanhui Geng ,  Pascal Poupart

IPC: G06F7/556 ,  H04L29/06 ,  H04L12/721 ,  H04L12/26 ,  H04L12/851

Abstract: A method for detecting a data flow type includes obtaining a header of a first data packet of a current data flow and a pattern vector of the current data flow from the header; comparing the at least one feature dimension in the pattern vector of the current data flow with a corresponding feature dimension in a pattern vector of at least one historical data flow, so as to obtain at least one pattern similarity of the current data flow; predicting a length of the current data flow according to the at least one pattern similarity of the current data flow and a length of the corresponding at least one historical data flow; and comparing the predicted length of the current data flow with a preset threshold, and determining whether the current data flow is a large data flow or a small data flow according to a comparison result.

公开(公告)号：US10187291B2

公开(公告)日：2019-01-22

申请号：US14980491

申请日：2015-12-28

Applicant: HUAWEI TECHNOLOGIES CO., LTD.

Inventor： Yanhui Geng ,  Kai Chen ,  Qiang Yang

IPC: H04L12/24 ,  H04L12/26 ,  H04L12/721 ,  H04L12/727 ,  H04L12/729

Abstract: The present application provides a path planning method and a controller. The method includes: acquiring data flow information of a to-be-transmitted job in a software-defined network, where the job includes at least one target data flow, and the data flow information of the job includes: a source address, a destination address, and a volume of each target data flow; and performing path planning according to the data flow information, and obtaining a job transmission path used to ensure that the job is transmitted in the software-defined network in a shortest job transmission time, where the job transmission path includes a transmission path corresponding to each target data flow in the job. The present application improves a data transmission speed of a job in an SDN network.

公开(公告)号：US20180375781A1

公开(公告)日：2018-12-27

申请号：US16127649

申请日：2018-09-11

Applicant: HUAWEI TECHNOLOGIES CO.,LTD.

Inventor： Zhitang Chen ,  Yanhui Geng ,  Hong Zhang ,  Kai Chen

IPC: H04L12/891 ,  H04L12/851 ,  H04L29/06 ,  H04L12/927 ,  G06N99/00

CPC classification number: H04L47/41 ,  G06F16/00 ,  G06N7/005 ,  G06N20/00 ,  G06N99/005 ,  H04L29/06 ,  H04L47/2441 ,  H04L47/803 ,  H04L69/22

Abstract: A coflow identification method includes: obtaining a weighted matrix by means of learning according to historical data in the network, where the weighted matrix is used to minimize a feature distance between data streams belonging to a same coflow and maximize a feature distance between data streams belonging to different coflows; computing a feature distance between any two data streams in the network according to metrics in the data stream layer data feature, the application layer data stream feature distance, the terminal aspect data feature distance, and the weighted matrix; and dividing the data streams in the network into several cluster sets by using a clustering algorithm and according to the feature distance between the any two data streams in the network, where each of the several cluster sets is a coflow.

公开(公告)号：US20180152386A1

公开(公告)日：2018-05-31

申请号：US15879452

申请日：2018-01-25

Applicant: HUAWEI TECHNOLOGIES CO.,LTD.

Inventor： Zhitang Chen ,  Fred Chi Hang Fung ,  Yanhui Geng

IPC: H04L12/851 ,  H04L12/753 ,  H04L12/931 ,  H04L12/751 ,  H04L12/715

CPC classification number: H04L47/2441 ,  H04L41/00 ,  H04L45/02 ,  H04L45/48 ,  H04L45/64 ,  H04L47/122 ,  H04L47/125 ,  H04L49/70

Abstract: A network data transmission method is provided. A switch device receives one or more data flows, classifies each of the received data flows into one of two classes according to data features of the data flow by using a decision tree model established by a flow table pipeline of the switch device. If a data flow belongs to a first class, the switch device reports the data flow to a controller, so that the controller computes a transmission path for the data flow. If a data flow belongs to a second class, the switch device obtains a transmission path for the data flow according to local flow table information, and transmits the data flow according to the obtained transmission path. Data flows are classified and filtered by using a switch, so as to improve network transmission efficiency while ensuring bearing capability of a network control system.

公开(公告)号：US20170195240A1

公开(公告)日：2017-07-06

申请号：US15465757

申请日：2017-03-22

Applicant: Huawei Technologies Co., Ltd.

Inventor： Zhitang Chen ,  Yanhui Geng ,  Pascal Poupart

IPC: H04L12/851 ,  G06F7/556 ,  H04L12/721 ,  H04L29/06 ,  H04L12/26

CPC classification number: H04L47/2483 ,  G06F7/556 ,  H04L43/00 ,  H04L43/16 ,  H04L45/70 ,  H04L69/22

Abstract: A method for detecting a data flow type includes obtaining a header of a first data packet of a current data flow and a pattern vector of the current data flow from the header; comparing the at least one feature dimension in the pattern vector of the current data flow with a corresponding feature dimension in a pattern vector of at least one historical data flow, so as to obtain at least one pattern similarity of the current data flow; predicting a length of the current data flow according to the at least one pattern similarity of the current data flow and a length of the corresponding at least one historical data flow; and comparing the predicted length of the current data flow with a preset threshold, and determining whether the current data flow is a large data flow or a small data flow according to a comparison result.