Data Mining Approach To Study
Quality Of Voice Over IP Applications
Author(s)
I. Miloucheva, D. Hetzer & A. Nassri
Abstract
Patterns focus on \“interesting” structures in data behaviour, which can be
abstracted and used for efficient understanding and analysis. This paper presents
a data mining technology aimed to assess characteristics of network connections
for Voice over IP (VoIP) communication based on analysis of structures of
Quality of Service (QoS) parameter time series data (end-to-end delay and
packet loss). The data mining approach for QoS parameter data is designed and
developed in the framework of EU IST INTERMON project [1]. It is used for
spatio-temporal analysis in the large scale inter-domain Internet.
We propose automated techniques to study network QoS parameter patterns
for VoIP communication, such as:
- \“Outliers” defining QoS parameter values exceeding \“thresholds”
corresponding to the rating factor R of the ITU-T E-model.
- End-to-end delay structures, used for appropriate choice of playback delay
adjustment algorithms.
Based on patterns, the network administrator can automatically evaluate the
ability of network connections for VoIP communication, and select appropriate
parameters for playback algorithms. The discussed data mining facilities for the
QoS parameter study for VoIP applications are shown using real measurement
data for inter-domain Internet connections collected in the INTERMON data
base.
Keywords: data mining, pattern, QoS parameter, end-to-end delay, packet loss,
VoIP, outlier.
Keywords
data mining, pattern, QoS parameter, end-to-end delay, packet loss, VoIP, outlier.
Related Book
Other papers in this volume
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