公开(公告)号：US20220150057A1

公开(公告)日：2022-05-12

申请号：US17114752

申请日：2020-12-08

Applicant: Beijing University of Posts and Telecommunications

Inventor： Hui YANG ,  Lin GUAN ,  Chao LI ,  Qiuyan YAO ,  Bowen BAO ,  Zhengjie SUN ,  Jie ZHANG

IPC: H04L9/08 ,  H04L9/32 ,  G06N3/08 ,  G06K9/62

Abstract: Disclosed is a data sharing method, including: building a trust alliance block chain, the trust alliance block chain comprising a main chain and at least one slave chain; each slave chain corresponding to a domain; and each domain comprising a leader node; establishing a virtual slave chain on the trust alliance block chain; designating, by the leader node in each domain, a node as a federated learning node; assigning, by the leader node in each domain, a virtual identity to the federated learning node to join the federated learning node to the virtual slave chain; and performing, by each federated learning node, a joint training on a local federated learning model using data generated in its own domain to establish a public federated learning model, through which data are shared among the domains. The present disclosure further provides a data sharing system, an electronic device and a storage medium.

公开(公告)号：US20220368650A1

公开(公告)日：2022-11-17

申请号：US17403479

申请日：2021-08-16

Applicant: Beijing University of Posts and Telecommunications

Inventor： Hui YANG ,  Bowen BAO ,  Qiuyan YAO ,  Chao LI ,  Zhengjie SUN ,  Jie ZHANG

IPC: H04L12/911 ,  H04L12/24 ,  G06N3/02

Abstract: Disclosed is a method of network resource allocation. The method includes: generating an adjacency matrix of nodes in a metropolitan area network (MAN) according to spatial adjacency relationships of the nodes; generating a network state feature matrix according to traffic information of each node; extracting traffic spatial features of the nodes from the adjacency matrix and the network state feature matrix through a traffic spatial feature extraction model; obtaining predicted traffic of the nodes from the traffic spatial features through a traffic prediction model; and performing a network resource allocation according to the predicted traffic of the nodes. Further, a device of network resource allocation and a non-transitory computer-readable storage medium are also disclosed.

公开(公告)号：US20220164795A1

公开(公告)日：2022-05-26

申请号：US17145674

申请日：2021-01-11

Applicant: Beijing University of Posts and Telecommunications

Inventor： Hui YANG ,  Shuai DONG ,  Qiuyan YAO ,  Bowen BAO ,  Chao LI ,  Zhengjie SUN ,  Jie ZHANG

IPC: G06Q20/40 ,  H04L9/06

Abstract: Disclosed is a cross-chain communication method. In this method, a first edge node of a first blockchain receives a first transaction request and validates the first transaction request; on condition that the first transaction request passes the validation, the first edge node will send the first transaction request to a notary node group; the notary node group determines at least one target notary node according to a preset criterion; the at least one target notary node validates the first edge node and a second edge node of a second blockchain corresponding to the first transaction request; and on condition that both the first edge node and the second edge node pass the validation, the first edge node will set up a cross-chain communication with the second edge node depending on the first transaction request to complete a cross-chain transaction. A cross-chain communication device and a storage medium are also disclosed.

公开(公告)号：US20220158913A1

公开(公告)日：2022-05-19

申请号：US17130302

申请日：2020-12-22

Applicant: Beijing University of Posts and Telecommunications

Inventor： Hui YANG ,  Zhengjie SUN ,  Qiuyan YAO ,  Bowen BAO ,  Chao LI ,  Jie ZHANG

IPC: H04L12/24 ,  H04L12/801 ,  G06N3/08 ,  G06N3/04

Abstract: Disclosed is a method for network slicing, which includes: determining a service keyword of a service intention after receiving the service intention from a user; converting the service intention into a network request according to the service keyword of the service intention on the basis of a pre-established mapping model, wherein, the network request comprises at least one network requirement index; determining a set of network slicing configuration parameters according to the network request and current network environment state on the basis of a network slicing model, wherein the network slicing model is a deep neural network model for determining network slicing configuration parameters according to a network request and a network environment state; and performing a network slicing according to the set of network slicing configuration parameters. The present disclosure also provides a device for network slicing and a computer readable storage medium.