Root cause analysis using Bayesian networks for a video streaming service

Detta är en Master-uppsats från KTH/Matematisk statistik

Sammanfattning: 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.

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