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Root cause analysis using Bayesian networks for a video streaming service
KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.
2019 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesisAlternative title
Grundorsaksanalys med hjälp av Bayesianska nätverk för en video strömningstjänst (Swedish)
Abstract [en]

In this thesis, an approach for localizing culprits of degradation of quality measures in an IPTV streaming service using Bayesian net-work is presented. This task is referred to as Root Cause Analysis(RCA). The objective of this thesis is to develop a model that is able to provide useful information to technicians by generating a list of probable root causes in order to shorten the amount of time spent on trouble shooting. A performance comparison is presented in Section Experimental results with Bayesian models such as Naive Bayes (NB),Tree Augmented naive Bayes (TAN) and Hill Climbing (HC) and the non Bayesian methods K-Nearest Neighbors and Random Forest. The results of the RCA models indicated that the most frequent most prob-able cause of degradation of quality is the signal strength of the user’s Wi-Fi that is reported at the user’s TV box.

Abstract [sv]

I detta examensarbete presenteras en metod för att lokalisera grundorsaken till nedgradering av kvalitet i en IPTV strömningstjänst. Denna uppgift refererar tillgrundorsaksanalys. Avsikten med denna tes är att utveckla en modell som kan tillförse tekniker med användarbar information genom att generera en lista med möjliga grundorsaker för att förkorta tiden som spenderas med felsökning. En prestandajämförelse är presenterad i Sektion Experimental results med de Bayesianska modellerna Naive Bayes (NB), Tree Augmented naive Bayes (TAN) och Hill Climbing (HC) samt de icke Bayesianska modellerna K-Nearest Neighbors och Random Forest. Resultatet av grundorsaksmodellerna indikerade att den mest frekventa mest sannolika grundorsaken till nedgradering av kvalitet är signal styrkan hos Wi-Fi nätverket vilket rapporteras i användarens TV-box.

Place, publisher, year, edition, pages
2019.
Series
TRITA-SCI-GRU ; 2019:094
Keywords [en]
Bayesian networks, Root cause analysis, applied mathematics
Keywords [sv]
Bayesianska nätverk, Grundorsaksanalys, tillämpad matematik
National Category
Probability Theory and Statistics
Identifiers
URN: urn:nbn:se:kth:diva-252717OAI: oai:DiVA.org:kth-252717DiVA, id: diva2:1320398
External cooperation
Ericsson
Subject / course
Mathematical Statistics
Educational program
Master of Science - Applied and Computational Mathematics
Supervisors
Examiners
Available from: 2019-06-04 Created: 2019-06-04 Last updated: 2019-06-04Bibliographically approved

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