1. Network and Systems Laboratory
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A Psychophysical Design
towards Fair Bandwidth
Allocation among VoIP Sessions
Chien-nan Chen 陳建男
Network and Systems Laboratory
Graduate Institute of Networking and Multimedia
National Taiwan University
2012/06/27
Advisors: Polly Huang and Hao-hua Chu
Copyright © 2012
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2. Network and Systems Laboratory
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Adaptation Psychophysics
Sending
QoS
Rate
Bandwidth
Measurement Fairness QoE
Rate Control Performance Assessment
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4. Network and Systems Laboratory
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Roadmap
Mechanism
Simulation
• QoS vs. QoE Design • Sustainable
• Sending Rate vs. • Rate control number of users • Call-based
Satisfaction • Sending rate • Accumulated simulation
quantization satisfaction • Comparison
with Skype
Modeling Analysis
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5. Network and Systems Laboratory
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Roadmap
Mechanism
Simulation
• QoS vs. QoE Design • Sustainable
• Sending Rate vs. • Rate control number of users • Call-based
Satisfaction • Sending rate • Accumulated simulation
quantization satisfaction • Comparison
with Skype
Modeling Analysis
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6. Network and Systems Laboratory
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Subjecting Codecs
AMR-WB SILK
 Widely used in mobile  The up-to-date codec
devices used by Skype
 Nine coding rates  Variable coding rates
(6.6~23.8 kbps) (5.6~40.6 kbps)
 Two sampling rates  Multiple sampling rates
(8 and 16 kHz) (8, 12, 16, 24 kHz)
 ECC embedded, extra  Wide spectrum of
bits for redundancy qualities, extra bits for
elaboration of details
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Roadmap
Mechanism
Simulation
• QoS vs. QoE Design • Sustainable
• Sending Rate vs. • Rate control number of users • Call-based
Satisfaction • Sending rate • Accumulated simulation
quantization satisfaction • Comparison
with Skype
Modeling Analysis
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10. Network and Systems Laboratory
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Design
6
5
4
MOS
3
2
MOS of fixed-quality tracks
1 ln(br-4.019)+1.515
0
0 5 10 15 20 25
Bitrate (kbps) 30 35 40 45
The exact mathematic model
Take only the log property
Divide the sending rate into levels with exponential differences
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11. Network and Systems Laboratory
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Mechanism
 Sending rate is exponentially quantized
into levels (which map to equally
separated MOSs)
 A call is only allowed to transmit data at
one of the level at any time
 Rate is raised to the highest level which
the available bandwidth allows
 Rate is dropped to the next lower level
when available bandwidth cannot sustain
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12. Network and Systems Laboratory
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Exponential Quantization (EQ)
 Simple and distributed
 Fairness: increases the number of calls
served under the same network capacity
 Performance: increases the accumulated
QoE of users served
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13. Network and Systems Laboratory
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Roadmap
Mechanism
Simulation
• QoS vs. QoE Design • Sustainable
• Sending Rate vs. • Rate control number of users • Call-based
Satisfaction • Sending rate • Accumulated simulation
quantization satisfaction • Comparison
with Skype
Modeling Analysis
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1. Fairness: Increase Users
Case 1: Available bandwidth increasing (by B)

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1. Fairness: Increase Users
Case 2: Available bandwidth decreasing

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Fairer is Better
 VoIP, like any other interactive networking
application, is a multi-party service
 Hoarding resource cannot improve your service quality
High Rate
Bad Tx Good Tx
Quality Quality
Good Rx Bad Rx
Quality Quality
Low Rate
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2. Performance: Increase Σ QoE

Rate change
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Normalized by the original rate
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P-Fair and Accumulated QoE

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Roadmap
Mechanism
Simulation
• QoS vs. QoE Design • Sustainable
• Sending Rate vs. • Rate control number of users • Call-based
Satisfaction • Sending rate • Accumulated simulation
quantization satisfaction • Comparison
with Skype
Modeling Analysis
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20. Network and Systems Laboratory
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Call-based Simulation
 We simulated 1,000~10,000 simultaneous calls in a
backbone link with running background traffic
 The background traffic is adopted from [Fraleigh 03]
which suggested a fractional Brownian motion with
124 Mbps average rate
 We simulated an OC-3 backbone link with 155 Mbps
capacity
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21. Network and Systems Laboratory
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Comparison
Three scenarios are simulated, where the calls adopt rate
adaptation scheme of:
1. Exponential Quantization
2. Naïve (baseline)
Changes in available bandwitdth is evenly
distributed to all calls, regardless of their qualities
3. Skype (reality check)
By manipulating the bandwidth and recording the
resulting rate of Skype, we manage to synthesize
adaptation scheme of Skype
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22. Network and Systems Laboratory
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Number of Calls Served
3000 100%
90%
2500
80%
Percentage of call supported
Number of supported calls
70%
2000
60%
1500 50%
40%
1000
30%
20%
500
10%
0 0%
Number of simultaneous calls Number of simultaneous calls
■ Exponential Quantization ■ Naïve ■ Skype
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23. Network and Systems Laboratory
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Accumulated QoE
 Problem: ITU never 8000
define MOS value for a 6000
forced dropped call 4000
Accumulate QoE
2000
 According to our
Naïve
Quant
0
model, MOS -2000
Skype
approaches –inf when -4000
bitrate is zero -6000
Number of simultaneous calls
 Our model outperforms
Accumulated QoE when forced drop=-1
others when the dropped
calls are given negative
scores
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24. Network and Systems Laboratory
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MOS Distribution
Exponential Quantization Naive Skype
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
1000 3000 5000 7000 9000
1000 3000 5000 7000 9000 1000 3000 5000 7000 9000
Number of simultaneous calls
Number of simultaneous calls Number of simultaneous calls
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25. Network and Systems Laboratory
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Conclusion
Aiming at devising a rate control mechanism for VoIP
calls, we investigate:
 How users perceive voice quality at different sending
rates with two popular speech codecs
 How one allocates the bandwidth such that we gain
more users than losing more
In result, we develop the simple and distributed EQ
scheme that:
 Increase the user population (naïve 334%; Skype 180%)
 Increase user’s satisfaction (naïve +2.3; Skype +1.0)
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27. Network and Systems Laboratory
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Define MOS of A Track
 Given a quantized-rate track, we now define its QoE.
 For a rate-changing incident as follows:
 MOS of every colored Rate fFLUC
blocks is then fFIX
weight-averaged by
their time durations
Time
a b c
min(a,b) min(b,c)
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28. Network and Systems Laboratory
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Define MOS of A Track
 For example, MOS of this particular track would be
Rate fFLUC
r1 f FIX
r2
r3 Time
a b c
 MOS = {fFIX(r3)*a/2+ fFLUC(r1,r3,a)*a+
fFIX(r1)*(b-a/2-c/2)+fFLUC(r1,r2,c)*c+fFIX(r2)*c/2}/(a+b+c)
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Proof of Approaching P-Fair

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Proof of P-Fair: Notations

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Properties

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P≥K
Theorem 1: In time interval [t0, t1], the total number
of level-up events P is no less than the number of
level-down events K.
 Total amount of bandwidth increased and decreased
during [t0,t1] are the same
 By the proof of favoring low calls, more bandwidth is
released by a random call decreasing its rate than
increasing
 The number of increasing adjustment (P) must be
more than the number of increasing adjustment (K)
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P’≥K’

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
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35. Network and Systems Laboratory
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Skype: Fixed Bandwidth
Available Sending
BW (kbps) Rate (kbps)
70
70 58.08947692
60
65 57.08036923
Sending Rate (kbps)
60 57.98412308 50
55 55.31864615 40
50 50.12886154 30
45 44.36393846 20
40 38.43926154 10
35 34.64332308 0
30 29.42424615 0 10 20 30 40 50 60 70 80
25 26.43064615 Available Bandwidth (kbps)
20 24.02375385
15 21.58646154
10 18.40947692
5 17.77181538
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36. Network and Systems Laboratory
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Skype: Bandwidth Change
Low BW (kbps) High BW (kbps) Diff (kbps) L->H(kbps/s) H->L (kbps/s)
25 30 5 0.6379381 2.0469237
25 35 10 0.7553864 1.62483514
25 45 20 0.8976954 5.60387293
25 55 30 1.4017246 5.89804405
30 35 5 0.4279915 2.4580033
30 40 10 0.7265226 3.14087255
30 50 20 1.2878194 2.59801165
35 40 5 0.4281306 2.381474
35 45 10 1.0751739 4.16207214
35 55 20 1.6227416 3.86504924
40 45 5 1.1018639 3.50748608
40 50 10 1.932563 2.73371261
40 60 20 2.7938022 2.84590066
45 50 5 0.8966093 1.85362606
45 55 10 0.7646173 2.94752985
50 55 5 0.71419 1.55146863
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37. Network and Systems Laboratory
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Granularity
3 Levels 5 Levels 9 Levels
60
50
bandwidth(kbps)
40
30
20
10
0
1 5 9 13 17 1 5 9 13 17 1 5 9 13 17
time(second) time(second) time(second)
■ Call #1 ■ Call #2 ■ Spare Bandwidth
Granularity 3 Levels 5 Levels 9 Levels
BW Consumption 19.811 kbps 26.780 kbps 29.794 kbps
BW Utilization 61.91% 83.69% 93.11%
Aggregated QoE 3.107 3.310 3.323
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