Open-­‐‑Source  Based  Prototype  for  QoS  
Monitoring  and  QoE  Estimation  in  
Telecommunication  Environments  	
Seb...
Introduction	
•  Implementation for Quality of Service (QoS) and
Experience (QoE) monitoring
•  Works in Real-time Transpo...
Environment	
	
•  Usage of Voice over IP (VoIP) increased over the last
years
•  It is not always possible to enforce QoS,...
Motivation	
•  ngnlab.eu targets distributed VoIP environments
and open-source based solutions
•  Commercial solutions are...
“Competition”
Theory	
•  E-model used to determine QoE (calculated acc.
several network parameters)
•  Objective (i.e., calculated) valu...
Correlation  between  MOS  
value  and  R-­‐‑Factor
Measured  Impairments  I	
•  One-way delay
•  Measured by halving
the Round-Trip-Time
(RTT) value of the voice
packets (es...
Measured  Impairments  II	
•  Packet loss probability
•  Determined by recording the sequence number of
each RTP packet th...
Measured  Impairments  III	
•  Packet loss distribution calculated acc. the patent
of McGowan
o  Overall packet loss proba...
Network  setup
Application	
•  Measurement probes
o  PCAP library captures packet for analysis
o  Perl script extracts required informati...
GUI
Measurement  setup
Results  I	
•  Non-degraded
measurement
•  Normal values
•  Delay in path 2+4 high
due to public network
Results  II	
•  Degraded
measurement
•  One-way delay on the
Internet higher (20x) in
paths 2+4
•  R-Factor decreased as
w...
Summary	
•  QoS and QoE can be measured using the designed
prototype
•  Implementation is scalable to smaller or larger Te...
Thank  you!	
Sebastian Schumann
seb.schumann@gmail.com
@s_schumann
Upcoming SlideShare
Loading in …5
×

Open-Source Based Prototype for Quality of Service (QoS) Monitoring and Quality of Experience (QoE) Estimation in Telecommunication Environments

1,537 views

Published on

This paper describes an implementation for monitoring the QoS and expecting the QoE of a voice communication in a Real-time Transport Protocol (RTP) based telecommunication environment. The resulting QoS parameters are evaluated; the QoE is determined with the E-Model and processed for graphical presentation. With the use of some open-source programming libraries, the presented prototype can be a helpful alternative for expensive measurement devices and is ready to be deployed in a widespread telecom environment at low cost. Presented at NGMAST 2011 in Cardiff, UK.

Published in: Technology, Education
  • Be the first to comment

  • Be the first to like this

Open-Source Based Prototype for Quality of Service (QoS) Monitoring and Quality of Experience (QoE) Estimation in Telecommunication Environments

  1. 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. 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. 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. 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. 5. “Competition”
  6. 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. 7. Correlation  between  MOS   value  and  R-­‐‑Factor
  8. 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. 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. 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. 11. Network  setup
  12. 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. 13. GUI
  14. 14. Measurement  setup
  15. 15. Results  I •  Non-degraded measurement •  Normal values •  Delay in path 2+4 high due to public network
  16. 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. 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. 18. Thank  you! Sebastian Schumann seb.schumann@gmail.com @s_schumann

×