Network failure real-time relativity analysing method and system

Abstract

Information of failure events from various network devices and service objects is written into original event list. Correlation analysis is carried out for events read by analyzing and controlling engine from the original event list according to levels of original event and selection of classes. The dynamic analytical algorithm synthetically handles information in each area such as scene of historical fault analysis, dynamic performance parameters of network, dynamic topology information and time character of event etc. comparing with prior art, the invention overcomes disadvantages of overlooking information of dynamic network state, dependent on preset rule and lack of auto study ability etc. The invented method provides effective correlation analysis, fault reason analysis and location in real time when storm of network fault happens.

Description

Technical field [0001] The invention belongs to the field of computer network communication, and in particular relates to a method and system for performing real-time correlation analysis on network failure events based on domain comprehensive information in network management. Background technique [0002] In computer and communication networks, when a certain device or service fails, a series of network events will be caused due to the close connection between the device, service and business, and the network management system responsible for monitoring the network will send event notifications through the device Or the polling monitoring of the network management system will find a large number of abnormal events, which will be reflected on the management interface of the network administrator through SNMP Trap, Syslog or Indication, thus appearing as a "network failure storm". Because this kind of fault storm often leads to a large number of events in a short period of t...

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Problems solved by technology

[0003] (1) It is impossible to dynamically consider the network topology link information;

[0004] (2) All input events are processed without selection, which is difficult to improve efficiency and consumes a lot of resources;

[0005] (3) The reasoning process relies too much on preset rules, feature tables or models, lacks automatic learning ability, and lacks the ability to adapt and deal with new situations outside the knowledge base;

[0006] (4) Observe the event sequence within a fixed time range, and cannot dynamically change the time range of correlation analysis;

[0007] (5) Lack of consideration of conditional probability and time factors in the analysis process;

[0008] (6) The network operating parameters obtained in real time cannot be combined in the analysis process based on static information

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