=Paper=
{{Paper
|id=Vol-2289/abstract1
|storemode=property
|title=None
|pdfUrl=https://ceur-ws.org/Vol-2289/abstract1.pdf
|volume=Vol-2289
|dblpUrl=https://dblp.org/rec/conf/safeprocess/Mazdziarz18
}}
==None==
<pdf width="1500px">https://ceur-ws.org/Vol-2289/abstract1.pdf</pdf>
<pre>
                   Alarm Correlation in Mobile
            Telecommunication Networks Based on the
                        Dice Coefficients
                                      Artur Maździarz ∗
                ∗
                 Ph.D. student, Systems Research Institute Polish Academy of
             Sciences, Nokia, Newelska street 6, 01-447 Warsaw Poland (e-mail:
                                artur.mazdziarz@gmail.com).

Abstract: The mobile telecommunication domain has recently been experiencing huge changes.
The introduction of new technologies and services (2G, 3G, 4G(LTE)), combined with a
multivendor environment distributed across one geographical area, brings a lot of challenges
in network operation routines. Network maintenance activities are becoming more and more
complicated and time consuming, as most of the tasks are carried out manually by experts
using raw network management information available in the management system via multiple
applications and direct database queries. The paper presents a methodology for alarm correlation
in mobile telecommunication networks based on the similarity coefficients Dice, Dice1 and Dice2
for binary representation of alarm symptoms from the network. The calculated values are treated
as probability measures of a relationship between alarms which can be used for constructing
Fault Propagation Model. The alarm correlation methodology based on a exponentially weighted
rolling average of Dice, Dice1 and Dice2 coefficients shows a satisfactory accuracy, speed and
reliability of correlation hypotheses. The methodology generates a reasonable Fault Propagation
Models for the Mobile Telecommunication Network. It is very effective from the computing
point of view and it is possible to run the algorithm on a PC. The proposed approach of
using the Dice, Dice1 and Dice2 coefficients for generating Fault Propagation Models works
very efficiently for models with several thousand symptoms (alarms). The values of conditional
probability estimates allow us to filter the most probable symptoms for network problems with
the right priorities. The binary temporal shift introduced into the algorithm at the level of four
seconds provides a good model of the time correlation window in mobile telecommunication
networks and makes it possible to correlate alarms more accurately. The exponentially weighted
rolling average of Dice, Dice1 and Dice2 coefficients simulates reasonably well the impact of
alarm propagation time on the value of correlation strength. The methodology is universal and
works regardless of the mobile technology which is used in the network (2G,3G,4G). It has been
discovered that the methodology provides also a good base for constructing alarm correlation
patterns. The patterns obtained could be used as predefined alarm correlation rules for reducing
the alarm correlation effort in the future for alarm data sets.

Keywords: Fault detection and diagnosis, Mobile Telecommunication Networks, Root Cause
Analysis, Dice, Dice1, Dice2 similarity coefficients.

</pre>