US 12,015,519 B2
Data processing method and apparatus, and computer storage medium
Zhongyu Wang, Nanjing (CN); Yuming Xie, Nanjing (CN); Wei Song, Nanjing (CN); and Zhenwei Zhang, Nanjing (CN)
Assigned to HUAWEI TECHNOLOGIES CO., LTD., Shenzhen (CN)
Filed by HUAWEI TECHNOLOGIES CO., LTD., Shenzhen (CN)
Filed on Mar. 10, 2022, as Appl. No. 17/691,736.
Application 17/691,736 is a continuation of application No. PCT/CN2019/117248, filed on Nov. 11, 2019.
Claims priority of application No. 201910860877.0 (CN), filed on Sep. 11, 2019.
Prior Publication US 2022/0200844 A1, Jun. 23, 2022
Int. Cl. H04L 41/0677 (2022.01); H04L 41/0631 (2022.01); H04L 41/12 (2022.01); H04L 41/14 (2022.01)
CPC H04L 41/0677 (2013.01) [H04L 41/0631 (2013.01); H04L 41/12 (2013.01); H04L 41/145 (2013.01)] 14 Claims
OG exemplary drawing
 
1. A data processing method, comprising:
extracting a plurality of knowledge graph triplets from network data of a target network, wherein the network data comprises a network topology of the target network and device information of a plurality of network devices in the target network, and the device information comprises one or more selected from interface configuration information, protocol configuration information, or service configuration information, the interface configuration information comprises an internet protocol (IP) address of an interface, a protocol type supported by the interface, and a service type supported by the interface, the protocol configuration information comprises an identifier of a protocol to identify the protocol, each knowledge graph triplet comprises two network entities and a relationship between the two network entities, and a type of the network entities is a network device, an interface, a protocol, or a service;
generating a knowledge graph of the target network based on the plurality of knowledge graph triplets;
when a fault occurs in the target network, obtaining abnormal events generated in the target network;
identifying, on the knowledge graph of the target network, abnormal network entities that generated the abnormal events in the target network;
determining one or more root-cause fault network entities from the abnormal network entities on the knowledge graph of the target network based on a fault propagation relationship among network entities; and
identifying the one or more root-cause fault network entities on the knowledge graph of the target network.