This document discusses the transition from Quality of Service (QoS) to Quality of Experience (QoE) in evaluating communication networks. It defines QoS as objective measures of network performance, while QoE is subjective and based on the end user's perspective. The document outlines methods for measuring QoS factors and conducting subjective user studies to determine QoE for applications like web browsing and video streaming. It presents results showing quality thresholds and the effects of varying network conditions on user satisfaction. Finally, it stresses the need for analytical QoE models to predict user experience based on network parameters and guide network provisioning to avoid over-provisioning.

1. The Path from QoS- to QoE-centric Management
of Modern Communication Systems
Jiri Hosek, Ph.D.
Youth School-Seminar, DCCN 2016
RUDN University, Moscow, November 24, 2016
*These slides are intended for educational purposes and include material
published by WISLAB group as well as available openly on the Internet.

2. Lecture’s Content
• Definition of network quality
• Quality of Service (QoS)
• Quality of Experience (QoE)
• Subjective evaluation of modern mobile applications

3. Evaluation of Service Quality
• Two main approaches how to measure the network
service quality
• Objective
• View from the network perspective
• Measuring of traffic parameters and their comparison with pre-
defined values
• Different services (applications) have different requirements
• Subjective (Relative)
• View of the end user
• Difficult and time-consuming
• MOS (Mean Opinion Score)
• Substitution of subjective evaluation by mathematical model

4. MOS Scale
• Used especially for multimedia transmissions
• Numerical expression of the human user’s view on the quality of the
network service

5. Key Network Traffic Parameters
• Dominant measurable parameters of network traffic
• Packet delay
• How long the transmission takes
• Packet delay variation (jitter)
• Difference between the delay of two consequent packets
• Packet loss
• How many packets are lost during the transmission
• Throughput
• Transmission speed (b/s)
• Key Performance Indicators (KPIs)

6. Uniform Network Traffic Treatment
• As default option in all older network technologies
• Seemingly fair approach
• Each data unit is of the same priority
• No possibility to prefer or defer any type of traffic
• “Best-effort” treatment
• No guarantees, just try

7. Differentiated Network Traffic Treatment
• Characteristic for modern network technologies
• Traffic classes
• Different requirements on transmission parameters
• Efficient operation of network services
• Identification of data units of different services/flows
• Guarantee of adequate treatment
• 2 basic QoS support mechanisms
• Integrated Service – IntServ
• Differentiated Services – DiffServ

8. Differentiated Services – DiffServ
• Offers different transmission parameters for different service types
• Every data packet is processed individually
• Fixed network resource sharing
• QoS functions implemented in each router
• Service guarantees
• Service-class based

9. DiffServ – Traffic Classification and Policing
• Traffic classification into an appropriate category
• Usually based on fields of IP and TCP/UDP header
• Differentiated Service CodePoint (DSCP) field in
the IP packet header
• Relative priorities
• Identifies service classes
• Traffic policing
• Ensures, that the incoming traffic satisfies the
declared parameters
• Service Level Agreement – SLA
• Network operator / end-user obligations

10. DiffServ – Packet Scheduling Techniques
• Main packet scheduling mechanisms
• First In First Out – FIFO queuing
• No QoS prioritization
• Priority Queuing – PQ
• Fair Queuing – FQ
• Weighted Fair Queuing – WFQ
FIFO
Priority Queuing

11. Application of DiffServ Mechanism
• Each network node
(router) is
performing QoS
functions
individually
• DiffServ routers
• Edge router
• Core router

12. Subjective Evaluation of Network Services
• Customers are demanding constantly increasing quality
of mobile services
• Modern mobile (multimedia) applications are highly
diverse
• Specific requirements and user expectations
• QoS-based evaluation and network control is not enough
anymore
• New investments for increasing network quality at all levels.
• Quality of (user) Experience (QoE)
• User eXperience (UX)
• Influenced by many factors
• Technical, socioeconomical, etc.

13. QoE Key Questions and Goals
(from network operator point of view)
• How the key network parameters affect the
quality of mobile service perceived by an end
user?
• How the type of application affects user‘s
evaluation?
• How long are end users willing to wait for specific
mobile service and being still satisfied?
• What are the “premium quality” and saturation
thresholds for the specific service?
• How to setup and control the mobile network to
avoid the over-provisioning?

14. Experimental Study of QoE in Mobile Networks
• The impact of following variables were investigated:
• End-user device:
• Smartphone Samsung Galaxy Nexus
• Tablet Samsung Galaxy Tab 10.1 inch
• Applications
• Web browsing, file download (DL), file upload (UL)
• YouTube video streaming
• Network and content parameters
• Bit rates (BR) in the range of 32kb/s to 16 Mb/s
• Initial loading delay (connection establishment) in the range of 0 to 11
seconds
• YouTube video resolution in the range of 320x180 to 1280x720
• Stalling effects with different duration and repetition
• More than 200 test scenarios evaluated by almost 300 test
participants

15. Experimental Study of QoE in Mobile Networks
– Methodology
• Laboratory environment
• Completely controllable system
• Test Methods: (rec. ITU-T P.800)
• Absolute Category Rating (ACR):
• Scaling: 5 grade MOS scale:
• 1: Bad
• 5: Excellent
• Acceptability rating:
• Question: Were you satisfied with tested quality?
• Binary answer: YES or NO

16. Mobile QoE – Automatic Assessment Tool – User
Interface
Questionnaire:Demographic data:Briefing phase:

17. Web: Sample Results – Quality Rating
• Web browsing, tablet

18. Web: Sample Results – Acceptability Rating
• Web browsing, smartphone
0
10
20
30
40
50
60
70
80
90
100
0 200 400 600 800 1000 1200
Acceptability[%]
BR [kbps]
0s 1s 3s 5s 7s 11s

19. Mobile Web QoE – Quality Thresholds
• We specified 3.7 MOS as a quality threshold for “premium quality” service.
• The saturation threshold refers to BR with zero initial loading delay and where quality rating
is not more increasing or achieved maximum quality rating or 4.5 MOS.
• This is very practical output in order to avoid quality overprovisioning.
Scenario Notebook Smartphone
Web 256 kbps 256 kbps
File DL 4 Mbps 4 Mbps
File UL 1 Mbps 1 Mbps
Scenario Notebook Smartphone
Web 512 kbps 256 kbps
File DL 4 Mbps 8 Mbps
File UL 4 Mbps 1 Mbps

20. Youtube: Sample Results (1)
• Quality rating vs. Resolution
• The subjective premium quality
threshold (3.7 MOS)
• Resolution [pixels]: 640 x 360
• Saturation threshold (4.5 MOS)
• Resolution [pixels]: 854 x 480
Overprovisioning area

21. Youtube: Sample Results (2)
• CDF of task’s leaving for infinity loading delay
50 % users wait
more than
104 / 44
seconds

22. Youtube: Sample Results (3)
• Acceptability rating results vs. single stalling duration – smartphone
1st level
quality
reduction
2nd level quality reduction

23. Youtube: Sample Results (4)
• Quality rating results vs. multiple stalling – smartphone
1st level
quality
reduction
2nd level quality reduction

24. Web: Analytical User Experience Prediction
• We need an adequate QoE prediction
models based on given results of
extensive QoE assessment.
• Analytical tools (regression analysis)
• Calculation of QoE value (MOS) for mobile
data services based on input parameters:
• Initial loading delay
• Throughput (bit rate)
a
ccBRc
ab
MOS D



 
2
1
0
~)(~1
)(

25. YouTube: Analytical User Experience Prediction
MOS 𝐷, 𝑅 =
2,7
1+9,5𝑒
0,1𝐷+
10,7
(0,01𝑅)2
𝑒−𝑁0,6 𝑆0,2
+1

26. Summary
• Future-generation mobile services are more user- /
service-oriented
• QoS-centric evaluation and control of modern
wireless networks is not enough
• User-centric / application-centric approach needs to be
implemented
• Complex evaluation from network- and user-perspective
as well
• QoE modelling is very demanded research topic
nowadays
• Not easy task due to high heterogeneity of modern
applications and their constant development
• Models need to be updated as users’ expectations are
growing
• Standardization in QoE assessment for new mobile
services is highly required

27. Thank you for your attention!
Questions?