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BEGIN:VEVENT
UID:534@lincs.fr
DTSTART;TZID=Europe/Paris:20200304T140000
DTEND;TZID=Europe/Paris:20200304T150000
DTSTAMP:20200305T090052Z
URL:https://www.lincs.fr/events/log-analysis-via-space-time-pattern-matchi
 ng/
SUMMARY:Log Analysis via Space-time Pattern Matching
DESCRIPTION:The increasing number of machines and technologies involved in
 existing infrastructures and networks hardens their management. Even if
 many monitoring solutions help to detect a faulty behavior\, having a clear
 understanding of its causes is not always straightforward\, especially if
 relevant information is scattered over logs issued by different software or
 hardware components. This paper proposes a new methodology inspired from
 pattern matching and able to find alarm correlations with or without prior
 knowledge about the monitored system. &nbsp\;The proposed data structure
 can store every observed pattern of correlated alarms by processing logs
 online. It can be queried to extract the patterns of alarms leading to an
 arbitrary failure. This paper comes with three main contributions. First\,
 we propose a framework able to represent alarm logs according to
 spatio-temporal dependencies. &nbsp\;Second\, we design a new scalable data
 structure\, able to store every observed pattern of alarms\, and validate
 it by simulation on real and artificial datasets. Third\, we show how to
 exploit this data structure for fault diagnosis.
CATEGORIES:Seminars,Youtube
LOCATION:Paris-Rennes Room (EIT Digital)\, 23 avenue d'Italie\, 75013
 Paris\, France
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=23 avenue d'Italie\, 75013
 Paris\, France;X-APPLE-RADIUS=100;X-TITLE=Paris-Rennes Room (EIT
 Digital):geo:0,0
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BEGIN:VTIMEZONE
TZID:Europe/Paris
X-LIC-LOCATION:Europe/Paris
BEGIN:STANDARD
DTSTART:20191027T020000
TZOFFSETFROM:+0200
TZOFFSETTO:+0100
TZNAME:CET
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