The Reality and Mythology of QoS and H.323 [email protected] [email protected].
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Transcript of The Reality and Mythology of QoS and H.323 [email protected] [email protected].
The Reality and Mythology of QoS and H.323
Overview
• H. 323 bounds testing
• QoS models
• Implications of applying models
• Engineering to need.
Test Motivation
• Abilene is trying to provide DiffServ EF
• Is H.323 suitable candidate for APS?
• DiffServ lacks hard bounds, it is totally probabilistic.
• What really would help? What are the performance bounds?
Video Artifacts
• Spatial Augmentation – Video artifacts are added to the picture. Objects appear that are not in the captured video such as video tiles.
• Spatial Depreciation – Parts of the picture or objects in the picture are missing.
• Temporal Distortion – Over time the “flow” of an event is distorted by missing data, in mild cases resulting in an inter-frame jerkiness. In more severe cases resulting in video freezing.
Video Artifacts
• Audio Augmentation – Audio artifacts added to audio stream such as pops, clicks and hiss.
• Audio Depreciation – Parts of the audio are missing.
Scope of H.323 Bounds Testing– What network conditions can be mapped to
certain qualities of video. – It can be highly subjective.– We did not desire to engage in a Cognitive
Science experiment. – Needed simple reproducible test procedure.
Test Procedure
• Still office scene, count the number of defects over a 60 second sample.
• Motion in scene and count the number of seconds needed to recover.
• Tested in a variety of setups – Point-to-point– MCU– Cascaded MCUs– Isolated Latency, Loss and Jitter
Network Emulator
• Operating System: Linux Mandrake 7.2 Kernel recompiled and optimized for the device to be a router.
• CPU: Pentium III 733Mhz• Memory: 256 MB.• Motherboard: Asus CUSLC2-C AGP4X• NICS: Intel Etherpro 10/100.• Emulator Software: Nistnet 2.1.0
Used to test H.323
• Verified Nistnet system prior to test.– Tested platform with SmartBits. – All parameters were met with in a +/- 1 msec
(Actual resolution ~.5msec)– With SmartBits we could verify switches etc. to
further validate our findings. Worst case is total accuracy within +/- 3msec.
Point-to-Point tests
• Latency does not matter. (holds true for all scenarios)
Drop Errored Seconds
0 0
17
0
4248
58 60 60 60 60
0 2 611
2530 35
60 60 60
010203040506070
0.01
%0.
10%
0.25
%0.
50%
0.75
%1.
00%
1.25
%1.
50%
1.75
%2.
00%
2.25
%
Percentage of Packets Dropped
Err
ore
d S
ec
on
ds
pe
r O
ne
Min
ute
Sa
mp
le
Appliance
NIC
Recovery Times
0 0.5 1 315
32
60 60 60 60 60
0 0.5 0.5 1 2 2 2 7
60 60 60
0
20
40
60
80
0.01
%0.
10%
0.25
%0.
50%
0.75
%1.
00%
1.25
%1.
50%
1.75
%2.
00%
2.25
%1
Percentage of Dropped Packets
Se
co
nd
s f
or
Re
co
ve
ry
Appliance
NIC
Jitter Errored Seconds
0 0 04
25
53
50
2535
20
57
0102030405060
10ms 20ms 30ms 40ms 50ms 60ms
IP Delay Variation
Err
ore
d S
ec
on
ds
P
er
1 M
inu
te
Appilance
NIC
Jitter Recovery Time
0 0 0.5 1 12
0 0.5 1 1
9
5
0
2
4
6
8
10
10ms 20ms 30ms 40ms 50ms 60ms
IP Delay Variation
Re
co
ve
ry T
ime
in
S
ec
on
ds
Appliance
NIC
MCU to Client Loss Test
0 0 616 16 11
60 60 60 60
0 012 12
21 21 23 23 23 23
0
20
40
60
80
0.01
%
0.10
%
0.50
%
0.75
% 1%
1.25
%
1.50
%
1.75
%
2.00
%
2.25
%
Percetage of Dropped Packets
Err
ore
d S
eco
nd
s p
er
On
e M
inu
te
Sam
pli
ng
Per
iod
Appliance
NIC
MCU to Client Recovery Time for Loss
0 1 1 1 5 3
60 60 60 60
0.5 1 3 4 5
60 60 60 60 60
010203040506070
0.0
1%
0.1
0%
0.5
0%
0.7
5%
1.0
0%
1.2
5%
1.5
0%
1.7
5%
2.0
0%
2.2
5%
Percentage of Dropped Packets
Re
co
ve
ry T
ime
in
S
ec
on
ds
Appliance
NIC
MCU to Client Jitter Errored Seconds
60 60 60 60 60 60
2134
24 28
60 60
0
20
40
60
80
10ms 20ms 30ms 40ms 50ms 60ms
IP Delay Variation in Milliseconds
Err
ore
d S
eco
nd
s p
er
On
e M
inu
te S
amp
ling
P
erio
d
Appliance
NIC
MCU to Client Recovery Time for Jitter
3828
5060 60 60
1827
60 60 60 60
010203040506070
10ms 20ms 30ms 40ms 50ms 60ms
IP Delay Variation
Re
co
ve
ry T
ime
s w
ith
6
0s
ec
Ma
x.
Appliance
NIC
One Way Loss Test
0 06
14 15 16 17 16 16 16
0 0
812
1521
24 23 23 23
05
1015202530
0.01
% 0.1
0.50
%0.
75%
1.00
%1.
25%
1.50
%1.
75%
2.00
%2.
25%
Percentage of Dropped Packets
Nu
mb
er o
f E
rro
rs p
er
On
e M
inu
te S
amp
le
Appliance
NIC
Recovery Time for One Way Packet Loss
0.5 1 1 2 2 3 3 3 3 30 0 4 10 12
60 60 60 60 60
0
20
40
60
80
0.01
%0.
10%
0.50
%0.
75%
1.00
%1.
25%
1.50
%1.
75%
2.00
%2.
25%
Percentage of Dropped Packets
Rec
ove
ry i
n
Sec
on
ds
per
On
e M
inu
te S
amp
le
Appliance
NIC
One Way Jitter with MCU
0 0 0 0 0 00 0 0
60 60 60
0
20
40
60
80
10ms 20ms 30ms 40ms 50ms 60ms
IP Delay VariationN
Um
be
r o
f E
rro
red
S
ec
on
ds
pe
r O
ne
M
inu
te S
am
ple
Appliance
NIC
One Way Jitter With MCU
0 1 2 1.5 2 2210 12
60 60 60
010203040506070
10ms 20ms 30ms 40ms 50ms 60ms
IP Delay Variation
Re
co
ve
ry T
ime
pe
r O
ne
Min
ute
Sa
mp
le
Appliance
NIC
Two Way Loss Via MCU
0 0
6
1217
14 15 13 12 12
0 0
12 1216
21 23 23 23 23
05
10152025
0.01
%0.
10%
0.50
%0.
75%
1.00
%1.
25%
1.50
%1.
75%
2.00
%2.
25%
Percentage of Dropped Packets
Err
ore
d S
ec
on
ds
p
er
On
e M
inu
te
Sa
mp
le Appliance
NIC
Recovery Time for Two Way Loss Via MCU
0.5 1 4 4 3 3 4 3 6 70.5 2 8 5 6 10
60 60 60 60
0
20
40
60
80
0.01
%0.
10%
0.50
%0.
75%
1.00
%1.
25%
1.50
%1.
75%
2.00
%2.
25%
Percenatge of Dropped Packets
Re
co
ve
ry T
ime
pe
r O
ne
Min
ute
Sa
mp
le
Appliance
NIC
Two Way Jitter with MCU
0
60 60 60 60 6060
10 7
60 60 60
0
20
40
60
80
10ms 20ms 30ms 40ms 50ms 60ms
IP Delay Variation
Err
ore
d S
eco
nd
s p
er
On
e M
inu
te S
amp
le
Appliance
NIC
Two WayJitter with MCU Recovery Times
0
20
2 2 2 23
10 10 108 8
0
5
10
15
20
25
10ms 20ms 30ms 40ms 50ms 60ms
IP Delay Variation
Rec
ove
ry T
ime
per
O
ne
Min
ute
Sam
ple
Appliance
NIC
Cascaded MCU One Way Test
0 0 0 0 0
60 60
17
60 60
0 0 0 0 0 0 0 0 0 0010203040506070
0.0
1%
0.1
0%
0.5
0%
0.7
5%
1.0
0%
1.2
5%
1.5
0%
1.7
5%
2.0
0%
2.2
5%
Pecentage of Dropped PacketsE
rro
red
Se
co
nd
s
pe
r O
ne
Min
ute
S
am
ple Appliance
NIC
Cascaded MCU One Way Recovery Times
0 0 0 0 3 1
15 1825
60 60
0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5010203040506070
0.01
%
0.10
%
0.25
%
0.50
%
0.75
%
1.00
%
1.25
%
1.50
%
1.75
%
2.00
%
2.25
%
Percentage of Lost Packets
Err
ore
d S
ec
on
ds
pe
r O
ne
Min
ute
Pe
rio
d
Appliance
NIC
Cascaded MCU Jitter One Way Test
0
20
40
60
80
10ms 20ms 30ms 40ms 50ms 60ms
IP Delay Variation
Err
ore
d S
ec
on
ds
pe
r O
ne
Min
ute
Sa
mp
le
Appliance
NIC
Cascaded MCU Jitter One Way Test
4052 60 60 60 60
0.5 0.5 0.5 0.5 0.5 0.5020406080
10ms 20ms 30ms 40ms 50ms 60ms
IP Delay Variationnote: network disruption was injected into MCU from
NIC side.
Rec
ove
ry T
ime
per
O
ne
Min
ute
Sam
ple
Appiance
NIC
End-to-end Delay Components
Compression Delay
Transmission Delay
Electronic Delay
Propagation Delay
Processing Delay
Queuing Delay
ResynchronizationDelay
DecompressionDelay
PresentationDelay
SENDER SIDE NETWORK RECEIVER SIDE
Delay Values
• Transmission Delay + Electronic Delay:
Modem delay = 40ms
Transmission delay = 10 chars over 56Kbps
= 80/56000bps = 1.4ms
• Switch Propagation Delay: <2ms
• Presentation Delay = 17ms
Encode and Decode Latency
MCU MCU
SWITCH END POINT 1 END POINT 2
METRONOME(PULSE
GENERATOR)
MIC I/P AUDIO O/P
OSCILLOSCOPEA BSCOPE I/P A:METRONOME I/PSCOPE I/P B:ENDPOINT 2 AUDIO O/P
Oscilloscope Waveforms
Experiment and Results
• Dialing Speeds: 256K, 384K, 512K, 768K
• Metronome setting: 113
• Propagation delay + Switch delay ~ 0
• Encode + Decode delay ~ 240ms
(independent of dialing speed)
• Delay through MCU ~120ms to ~200ms
(delay increasing with dialing speed)
Network Requirements
• Latency – users may find annoying but the it does not break the protocol.
• Loss – Can tolerate some loss, must be below 1% in p-2-p and 0.75% in MCU
• Jitter – Very jitter intolerant. For 30 Fps must be lower than ~33 msec. Seems very intolerant in cascaded MCU scenario.
Network Calculus 101
• All functions are cumulative distribution functions, i.e. wide-sense increasing.
• Uses min-plus Algebra.• Uses classes of primitive functions to
describe various network behaviors• Employs convolution and deconvolution
with primitives to arrive at meaningful conclusions.
Models
• IntServ – Has the necessary per flow state but is not here yet.– It also probably has many unforeseen
maintenance and administrative issues. (see next section).
– Experience from ATM SVCs suggests many scalability issues. Possible solutions include MPLS or Policy routing.
Models
• Any E-2-E solution has scalability problem in the sense that in packet switched networks the solution vector is more than number of hops and delay etc.
• x-> <= Ax->+α->
• In other words it is also a function of topology. (More in DiffServ).
.Source: Network Calculus: A Theory of Deterministic Queuing Systems for the Internetby Jean-Yeves Le Boudec & Patrick Thriran, Springer-Verlog, Berlin Heidelberg, 2001.
Models
• DiffServ lacks the per flow state necessary for tight performance bounds because…..
• β*1(t) = [β(t)- α2(t)] Where β is the rate-latency
function. βR,T(t) = R[t-T]+ i.e. Service Curve.
• b*1 = b1 + r1T +r1(b2+r2T/R-r2) Where b is a
component of the Affine function γ r,b(t) = b+rt if t>0.
Source: Network Calculus: A Theory of Deterministic Queuing Systems for the Internet
by Jean-Yeves Le Boudec & Patrick Thriran, Springer-Verlog, Berlin Heidelberg, 2001.
Models
• V ~ 0.564 for bounded delay so when v0
converges to V the latency bound explodes to infinity. For vl = ΣiЭm ri/Cl. Wherev = link utilization, i=flow, r = rate and C = service rate.
Source: Network Calculus: A Theory of Deterministic Queuing Systems for the Internetby Jean-Yeves Le Boudec & Patrick Thriran, Springer-Verlog, Berlin Heidelberg, 2001.
Engineering to the need
• What realistically can we do?– It depends on ones network.– Appropriate queuing for congested links for
maybe a single to only a few flows.– Packet shaping on receiver with a Greedy
Packet Shaper.GPS will not increase latency or
buffering requirements if and only if network was previously lossless.