Managing Network Alarms

A method for handling alarms in a communications network, the method comprising a network node:

• for a set S of alarms collected in the communications network during a time period T:
• obtaining a first type of alarms and their time of arrival from the set;
• applying Kernel Density Estimation on the first type of alarms, by applying a distribution function to each occurrence of the first type of alarms, thereby obtaining a distribution function for the first type of alarms over the time period T;
• obtaining a second type of alarms and their time of arrival from the set S;
• applying Kernel Density Estimation on the second type of alarms, by applying a distribution function to each occurrence of the second type of alarms, thereby obtaining a distribution function for the second type of alarms over the time period T;
• determining a maximum correlation between the distribution function for the first type of alarms and the distribution function for the second type of alarms;
• determining a time shift between the distribution function for the first type of alarms and the distribution function for the second type of alarms associated with the maximum correlation;
• obtaining an indication of a mutual relation between the first and second types of alarms based on the maximum correlation and the time shift;
• comparing the obtained indication with at least a first threshold;
• and managing the alarm types based on the comparison.

A network node for handling alarms in a communications network, the network node comprising:

• processing circuitry;
• memory containing instructions executable by the processing circuitry whereby the network node is operative to:
• obtain a first type of alarms and their time of arrival from a set S of alarms collected in the communications network during a time period T;
• apply Kernel Density Estimation on the first type of alarms, by applying a distribution function to each occurrence of the first type of alarms, thereby obtaining a distribution function for the first type of alarms over the time period T;
• obtain a second type of alarms and their time of arrival from the set S;
• apply Kernel Density Estimation on the second type of alarms, by applying a distribution function to each occurrence of the second type of alarms, thereby obtaining a distribution function for the second type of alarms over the time period T;
• determine a maximum correlation between the distribution function for the first type of alarms and the distribution function for the second type of alarms
• determine a time shift between the distribution function for the first type of alarms and the distribution function for the second type of alarms associated with the maximum correlation;
• obtain an indication of a mutual relation between the first and second types of alarms based on the maximum correlation and the time shift;
• compare the obtained indication with at least a first threshold;
• and manage the alarm types based on the comparison.

A non-transitory computer readable recording medium storing a computer program product for handling alarms in a communications network, the computer program product comprising software instructions which, when run on processing circuitry of a network node, causes the network node to:

• for a set S of alarms collected in the communications network during a time period T:
• obtain a first type of alarms and their time of arrival from the set;
• apply Kernel Density Estimation on the first type of alarms, by applying a distribution function to each occurrence of the first type of alarms, thereby obtaining a distribution function for the first type of alarms over the time period T;
• obtain a second type of alarms and their time of arrival from the set S;
• apply Kernel Density Estimation on the second type of alarms, by applying a distribution function to each occurrence of the second type of alarms, thereby obtaining a distribution function for the second type of alarms over the time period T;
• determine a maximum correlation between the distribution function for the first type of alarms and the distribution function for the second type of alarms;
• determine a time shift between the distribution function for the first type of alarms and the distribution function for the second type of alarms associated with the maximum correlation;
• obtain an indication of a mutual relation between the first and second types of alarms based on the maximum correlation and the time shift;
• compare the obtained indication with at least a first threshold;
• and
• manage the alarm types based on the comparison.