Event correlation

A network management system for automatically processing alarm signals, said system comprising:

• means for generating alarm signals generated by monitors as a result of alarm conditions occurring in a plurality of components of a telecommunications network,
• receiving means for receiving said alarm signals,
• storing means for storing historical data including a representation of the times at which alarm conditions occur in the telecommunications network during a reference time period,
• correlating means for correlating alarm conditions identified as occurring within a predetermined temporal window,
• said correlating means including means for determining the statistical probabilities of pairs of the identified alarm conditions occurring by chance within the some temporal window, and
• means for displaying at least some of the statistical probabilities determined by the correlating means.

A self-learning adaptive network management system comprising:

• network condition detectors distributed within the network and disposed to generate respectively corresponding alarm signals in response to detected abnormalities;
• an alarm monitoring means connected to receive said alarm signals and to assign the occurrence of each to an associated time;
• a historical data storage means connected to receive and store historical data representing the identity of alarm signals historically received in the past from the network;
• correlation means connected to process said stored historical data and generate statistical data therefrom representing the probability of a predetermined plurality of predetermined alarm signals independently occurring within the same time window by chance;
• and
• means for using said statistical data to identify and display concurrently received new incoming alarm signals that are most probably not independent occurrences but, instead, are most probably inter-dependent related alarm conditions.

A method for self-learning adaptive network management, said method comprising:

• generating alarm signals in response to detected abnormalities within the network;
• receiving said alarm signals and assigning the occurrence of each to an associated time;
• storing historical data representing the identity of alarm signals historically received in the past from the network;
• processing said stored historical data to generate statistical data representing the probability of a predetermined plurality of predetermined alarm signals independently occurring within the same time window by chance;
• and
• using said statistical data to identify and display concurrently received new incoming alarm signals that are most probably not independent occurrences but, instead, are most probably inter-dependent related alarm conditions.