decompiling qoe

© 2015 UZH, CSG@IFI

Decompiling QoE

Christos Tsiaras, Burkhard Stiller

Department of Informatics IFI, Communication Systems Group CSG, University of Zürich UZH [tsiaras,stiller]@ifi.uzh.ch

ETSI workshop, Vienna, Austria, October 22, 2015

Background QoE Models

Proposed Solution Example


QoE Fundamentals

!  QoE is affected by multiple variables –  Each variable has different importance

!  Each variable affects differently each user’s QoE –  Each variable also affects the user differently in each service

!  The QoE concept is a mess! –  Because is a user&service-centric concept

!  Mapping human brain into math is challenging –  And fun "

QoE = f (user, service,X = {QoS1,…,QoSk,…,QoSN})


QoE in IPTV Services (Bandwidth, Price)

T. Hayashi, A. Takahashi, Nippon Telegraph and Telephone Corporation (NTT), Japan, "QoE Assessment Method for Video Quality and Pricing in IPTV Services", European Telecommunications Standards Institute (ETSI) Workshop, 17-19 June 2008, Prague, Czech Republic.


QoE in VoIP (Latency)

O3b Networks, Sofrecom, “Why Latency Matters to Mobile Backhaul”


QoE in VoIP (Hops in WMNs)

A. Chhabra, Grupal Singh, "Performance Evaluation and Delay Modeling of VoIP Traffic over 802.11 Wireless Mesh Network", International Journal of Computer Applications, Vol. 21, No. 9, pp. 0975 – 8887, May 2011.


QoV: QoE in Video (IPTD & IPLR)

S. Aroussi, T. Bouabana-Tebibel, A. Mellouk, "Empirical QoE/QoS correlation model based on multiple parameters for VoD flows," Global Communications Conference (GLOBECOM), 2012 IEEE, pp.1963-1968, 3-7 Dec. 2012

2/n-D

IP packet Transfer Delay

IP p

acke

t Los

s R

atio


QoE Models Market - IQX Hypothesis IQX :QoE =α ⋅e−β⋅QoS +γ

!  1 degree of freedom –  β: curve gradient

!  α and γ define the min and max MOS

!  Describes antitonic MOS only


QoE Models Market – QoV QoV :QoE =α ⋅eβ0+β1⋅QoS1+β2⋅QoS2+…

!  One degree of freedom per variable –  β1, β2, ...

!  Describes multiple but only antitonic MOS !  β0 has to be defined based on the number of variables

that are involved –  The generic QoE equation do not reproduce the same QoE

equation if only one QoS parameter is examined •  Example that makes physics beautiful (Lorentz factor disappears)

m =m0

1− u2

c2

u << c⇒

u2

c2= 0 ⇒ m =m0


Proposed Solution An Axiomatic QoE Model (AQX)

!  Formalizing QoE in steps 1.  Identify the variables that affect QoE 2.  Characterize those variables

•  Isotonic Variables (IVs) - The more you have the better it is •  Antitonic Variables (AVs) - The more you have the worst it is

3.  Select the ideal/desired/expected/agreed value of a variable

4.  Considering the service specifications select the best and the worst values of the variable

5.  Identify the effect of each variable’s variation •  Influence factors

6.  Identify the importance of each variable


AQX

ea (x) = 4e−

xx0

"

#$

%

&'m

ln43+1QoE equation for AVs

ei (x) = 4(1− e−

xx0

"

#$

%

&'m

ln 4)+1QoE equation for IVs

E(X) =1+ 4e i∨a( ) xk( )−1

4

#

$%%

&

'((k=1

N

∏wk

Generic QoE equation

Importance factor Step 6

Influence factor Step 5

Expected value Step 3

Variables selection Step 1

Variables characterization Step 2

QoE QoE-related variables values

Best and worst values Step 4


(Parenthesis)

IQX :QoE =α ⋅e−β⋅QoS +γ

AQX :QoEa = h ⋅e(−λa⋅QoS

m ) +µ

h =M −µ λa =QoS0−m ⋅ ℓn h

e0 −µ

#

$%

&

'(

αα h

h: width of the given options

βγ γµ

µ: the minimum score

λ: a reference point (QoS,QoE)

β λ


Is QoE Served?


!  Is it possible to define importance factors (w) without: –  Surveys? –  Curve fitting?

w

Open Questions


Example – Steps 1 and 2

!  Scenario: Internet plans of an ISP for home customers in some places in Switzerland

!  Step 1: Variables identification –  Uplink bandwidth –  Downlink bandwidth –  Price

!  Step 2: Variables characterization –  IVs

•  Uplink bandwidth •  Downlink bandwidth

–  AVs •  Price


Example – Step 3

!  Step 3: Select the ideal/desired/expected/agreed value of a variable –  Assume a customer selected the “Internet 50” option –  Ideal values based on the SLA

•  Uplink bandwidth: 5 Mbit/s •  Downlink bandwidth: 50 Mbit/s •  Price: 59 CHF/month


Example – Step 4

!  Step 4: Select the best and worst values per variable –  Best values

•  Uplink bandwidth: 15 Mbit/s •  Downlink bandwidth: 250 Mbit/s •  Price: 0 CHF/month

–  Worst values •  Uplink bandwidth: 0.2 Mbit/s •  Downlink bandwidth: 2 Mbit/s •  Price: 89 CHF/month


Example – Steps 5 and 6

!  Step 5: Identify the effect of each variable’s variation –  When a customer is starting to get annoyed/getting pleased?

•  Estimate/Assume/Extract this information from the Customer Care department statistics about report of problems

–  E.g., 50% less than expected bandwidth dissatisfies a customer –  E.g., 25% discount would satisfy a dissatisfied customer

!  Step 6: Identify the importance of each variable –  How a customer selects a plan in this scenario?

•  Estimate/Assume/Extract through a survey: –  50% based on the price –  30% based on the downlink bandwidth –  20% based on the uplink bandwidth


Q&A AQX Model paper

LCN 14 AQX in VoIP paper IFIP Networking 15

http://tiny.uzh.ch/da http://tiny.uzh.ch/db

decompiling qoe

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