Chinese Academy of Sciences

Beijing Hili Technology Co. Ltd.

Shanghai 3Ntv Network Technology Co. Ltd.

Huawei Technologies Co., Limited

Haojiang Deng

Gang Cheng

Jun Chen

Wei Li

Qing Zhang

Jun Wang

Jinlin Wang

Lingfang Wang

Xiaozhou Ye

Jiali You

Weining Qi

Yiqiang Sheng

Xue Ping Liu

Zhengzhong Du

Lijing Xu

Yi Liao

Jianfeng Xu

Shenghu Sang

Zhaolin Liu

Qin Yan

A method for propagating a movement event message of a network entity, including: step 1) a network device maintaining a historical forwarded information list, wherein a network device capable of receiving a movement event message from an external system or device maintains an uplink port information table; step 2) after receiving the message, the network device performs matching using the table to obtain a forwarding port and forwarding information of the message, and constructs a movement event forwarding message using the information and forwards through the forwarding port; and step 3) after a device receives the message, searching for a matching forwarding port and forwarding information of the message in the information list, modifying the message using the forwarding information, and forwarding the modified message through the forwarding port. The method is able to propagate a movement event message to a network device responsible for related data transmission and forwarding.

Method for propagating movement event message of network entity

A query enhancement system for constructing an elastic field based on a time delay, including: dividing a network node to obtain a set of containers composed of several containers, wherein the containers are nested and each container includes a management node for performing node organization, neighbor maintenance and query services within the container. Further, a query enhancement method for constructing an elastic field based on a time delay includes: carrying out same-layer non-intersection full-coverage division on a network node to obtain a set of containers that are nested, and execute a query flow without a given low time delay requirement which uses an existing query technique and a nearby query flow with a given low time delay requirement which uses a distributed nearby querying method to carry out a nearby query; with an actual query time delay index Ti less than the requirement of an upper time delay limit Ts.

Query enhancement system and method for constructing elastic field based on time delay

A ICN packet forwarding method, including: step 1) maintaining, by a network forwarding device, a network entity ID association state table, which is used for recording a state of the binding relationship between a network entity ID and a network address to which the network entity is associatively bound; after a network address binding relationship of the network entity changes due to location movement thereof, adding or updating, by the network forwarding device, a record of the network entity in the network entity ID association state table according to notification information of the network entity; and step 2) upon receipt of an ICN packet, by the network forwarding device, determining whether the ICN packet needs to be processed, according to information of the current network entity ID association state table; if yes, forwarding after processing the ICN packet; otherwise, directly forwarding the packet.

ICN packet forwarding method

A method for generating a nested container with no intersection and same layer full coverage, including: giving a right undirected graph G(V, E, W) and network measurement index set {Ti} for dividing nodes in G, each network measurement index Ti corresponding to a Ci layer container set {Ci k}; deleting an edge weighing greater than Ti, and segmenting G into subgraphs, each a connected component; setting all nodes in the subgraph Gcm not in the Ci layer container as set L; selecting one node from set L as current anchor aj; starting with anchor aj, performing breadth-first search on all nodes in L and Ci+1 layer container containing aj with the path communicated therewith less than Ti forming a Ci layer container with anchor aj; setting j'=j+1, determining whether L is a null set; setting m=m+1, determining whether all subgraphs are processed; setting i=i&#x2212;1, and determining whether i=1 is satisfied.

Method for generating nested container with no intersection and full coverage in the same layer and readable storage medium

A fast query method for a mobile network entity dynamic location information, using a distributed container hierarchical nested structure to process registration and queries for location information, includes: after a network entity connects to a network attachment point after moving and obtains a new network address assignment, determining a series of a registered container, and then registering new location information corresponding to where the network entity is currently located, the location information containing at least current network address information; when a network forwarding device learns that the network entity is currently un-reachable, querying the new location information of the network entity from the container where the network entity was located before moving; and the container where the network entity was located before moving, after receiving the query request, obtains the new location information of the network entity by searching in the container and in a peer neighboring container set.

Fast query method for dynamic location information of mobile network entity

A big data processing method based on a deep learning model satisfying K-degree sparse constraints comprises: step 1), constructing a deep learning model satisfying K-degree sparse constraints using an un-marked training sample via a gradient pruning method, wherein the K-degree sparse constraints comprise a node K-degree sparse constraint and a level K-degree sparse constraint; step 2), inputting an updated training sample into the deep learning model satisfying the K-degree sparse constraints, and optimizing a weight parameter of each layer of the model, so as to obtain an optimized deep learning model satisfying the K-degree sparse constraint; and step 3), inputting big data to be processed into the optimized deep learning model satisfying the K-degree sparse constraints for processing, and finally outputting a processing result. The method in the present invention can reduce the difficulty of big data processing and increase the speed of big data processing.

Big data processing method based on deep learning model satisfying k-degree sparse constraint

A distributed node intra-group task scheduling method includes: step) collecting resource state information and history service information about each node in a group; step) receiving a service request command and parsing the request command to obtain a request task; step) according to the resource state information and history service information about each node, calculating the resource utilization rate increment after each node in the group loads a task and the occupation condition of each kind of resource in the group; and according to a principle of making the resource utilization rate increment of each node in the group as low as possible and the occupation of each kind of resource in the group as balanced as possible, selecting service execution nodes in the group, and providing the request task by the selected service execution nodes.

Distributed node intra-group task scheduling method and system

A system and method for providing an on-site service includes a plurality of nodes, each containing: a neighborhood node set generation module, for generating a neighborhood node set on the basis of the bidirectional link bandwidth between a local node and a neighboring node; a neighborhood information index table generation module, for generating a neighborhood information index table of the local node; a candidate service point selection module, for selecting according to a selection function a candidate service node from the set of neighboring nodes; the definition of the selection function being: for a current service request, computing the difference between the QoS of the neighboring node i executing the service request and the QoS of the local node executing the service request; if the computed difference is smaller than a set threshold, the neighboring node i serving as the candidate service node; a service scheduling module, for receiving status information and feedback information provided in real time by the candidate service node, and selecting, on the basis of this information, a candidate node or the local node to serve as the service-executing node.

System and method for providing an on-site service

Growing community of inventors

Beijing, China

Haojiang Deng