The document presents an open-source prototype developed for monitoring Quality of Service (QoS) and Quality of Experience (QoE) in telecommunications, particularly in Voice over IP (VoIP) environments. It details the system's ability to analyze various QoS parameters in real-time and offer informative results through a central reporting unit, addressing the challenges of unmanaged networks. The implementation is scalable and can compete with commercial solutions, providing tools for diagnosing network impairments and enhancing monitoring capabilities.

1. Open-­‐‑Source Based Prototype for QoS
Monitoring and QoE Estimation in
Telecommunication Environments
Sebastian Schumann
Slovak University of Technology
Bratislava, Slovakia
Cardiff, UK – 15. September 2011

2. Introduction
• Implementation for Quality of Service (QoS) and
Experience (QoE) monitoring
• Works in Real-time Transport Protocol (RTP) based
telecommunication environments
• Analysis
o QoS parameters are evaluated
o QoE is determined with the E-Model
• Output
o R-Factor, one-way delay, packet-loss probability
o Graphical representation

3. Environment
• Usage of Voice over IP (VoIP) increased over the last
years
• It is not always possible to enforce QoS, esp. in
unmanaged networks
• Size of measured network does not matter
• Measurement system
o Measurement points (probes) are distributed
o Central reporting unit collects and evaluates the data
• Focus on widespread networks, not system
components

4. Motivation
• ngnlab.eu targets distributed VoIP environments
and open-source based solutions
• Commercial solutions are expensive, only for
operators
• Main goals
o Easy but flexible measurement design
o A non-intrusive online monitoring
o Informative results
o Ability to determine the geographical and technical
source of degradations

5. “Competition”

6. Theory
• E-model used to determine QoE (calculated acc.
several network parameters)
• Objective (i.e., calculated) value can be mapped
to the subjective Mean Opinion Score (MOS)
• Impacts on speech quality are
o One-way delay
o Packet-loss probability
o Packet-loss distribution
o Speech codec
• Measurement and evaluation of values allow
calculation of QoS/QoE during the call

7. Correlation between MOS
value and R-­‐‑Factor

8. Measured Impairments I
• One-way delay
• Measured by halving
the Round-Trip-Time
(RTT) value of the voice
packets (estimation)
• Both directions possible
• RTT determination using
measured values
o Time-stamp in PCAP
o Time-stamp in RTCP
• RTT1=A2-A1-D2
• RTT2=A3-A2-D3
DLSR .. delay sender report
A1 .. 1st SR passes ME
A2 .. following SR
D2 .. DL btw reception of SR1 and transmission of SR2

9. Measured Impairments II
• Packet loss probability
• Determined by recording the sequence number of
each RTP packet that passes the ME
• The loss probability is updated after every 100 RTP
packets
o The time distance is a good balance between the applied
load on the ME, the network load, and the actuality of the
measurement results on the EE

10. Measured Impairments III
• Packet loss distribution calculated acc. the patent
of McGowan
o Overall packet loss probability (Ppl)
o Average length of all loss sequences
• Speech codec is determined by parsing the Session
Description Protocol (SDP) during the session
establishment procedure
• Knowledge is important in relation to the used
compression method and its robustness against
packet loss (packet loss robustness factor)

11. Network setup

12. Application
• Measurement probes
o PCAP library captures packet for analysis
o Perl script extracts required information from each packet
o HTTP is used to exchange measured parameters
• Central reporting unit
o Java application
o Real-time monitoring with three detail levels (monitoring
unit, call, details)
o Adjustable color indication when pre-set thresholds are
reached

13. GUI

14. Measurement setup

15. Results I
• Non-degraded
measurement
• Normal values
• Delay in path 2+4 high
due to public network

16. Results II
• Degraded
measurement
• One-way delay on the
Internet higher (20x) in
paths 2+4
• R-Factor decreased as
well
• Knowing network and
taking packet loss into
account, low upload on
office B is determined

17. Summary
• QoS and QoE can be measured using the designed
prototype
• Implementation is scalable to smaller or larger Telco
networks (probes can be distributed accordingly)
• Implementation can compete with professional
equipment to a certain extent
• Extensions open but easily possible
o Alarms
o Visual network status display in real-time
o Follow-up calls for neg. quality calls
o Recording of call samples possible as well

18. Thank you!
Sebastian Schumann
seb.schumann@gmail.com
@s_schumann