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A QoS approach for Multimedia Consumer Terminals - A case for Conditionally Guaranteed Budgets -. Reinder J. Bril. 23-11-2004. Multimedia Consumer Terminals and QoS. Multimedia Consumer Terminals audio/video: perception is key high volume electronics: cost-constrained - PowerPoint PPT Presentation
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Reinder J. Bril, [email protected]/e Informatica, System Architecture and Networking
1
Reinder J. Bril
A QoS approach forMultimedia Consumer Terminals
- A case for Conditionally Guaranteed Budgets -
23-11-2004
Reinder J. Bril, [email protected]/e Informatica, System Architecture and Networking
2
Multimedia Consumer Terminals and QoS
• Multimedia Consumer Terminals– audio/video: perception is key– high volume electronics: cost-constrained– requires average-case resource allocation
• High quality audio and video:– have real-time requirements
• Quality of Service (QoS)– “collective effort of service performances that
determine the degree of satisfaction of the user of that service”(International Telecommunications Union)
Reinder J. Bril, [email protected]/e Informatica, System Architecture and Networking
3
Quality of Service Resource Management
(QoS-RM)
Scalable Video Algorithms
(SVA)
V-QoS
University of Madrid (dit/UPM)
University of Illinois at Urbana- Champaign (UIUC)
University of Mannheim
University of St. Petersburg
ITEA/Europa, ITEA/Robocop, OZONE, …
Multi-disciplinary QoS approach
Reinder J. Bril, [email protected]/e Informatica, System Architecture and Networking
4
Overview
• Multimedia Consumer Terminals• A QoS approach• Conditionally Guaranteed Budgets• Conclusion
Reinder J. Bril, [email protected]/e Informatica, System Architecture and Networking
5
Overview
• Multimedia Consumer Terminals– Media processing from dedicated HW to SW– Platforms are resource constraint– High quality video has real time requirements
• A QoS approach• Conditionally Guaranteed Budgets• Conclusion
Reinder J. Bril, [email protected]/e Informatica, System Architecture and Networking
6
Overview
• Multimedia Consumer Terminals• A QoS approach
– Adaptive applications– Budget-based resource manager– Control hierarchy
• Conditionally Guaranteed Budgets• Conclusion
Reinder J. Bril, [email protected]/e Informatica, System Architecture and Networking
7
Overview
• Multimedia Consumer Terminals• A QoS approach• Conditionally Guaranteed Budgets
– Resource allocation conflict– Extension of QoS approach– Analysis
• Conclusion
Reinder J. Bril, [email protected]/e Informatica, System Architecture and Networking
8
Multimedia Consumer Terminals
DVD CDxfront end
YC interface
IEEE 1394interface
DVB Tuner
Cable modem
CVBSinterface
VGA
RF Tuner
Focus:
Receivers in broad-cast environments
High-quality video applications
Reinder J. Bril, [email protected]/e Informatica, System Architecture and Networking
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Traditional High-End TV Architecture
TXT CPUacq control
progROM
RAM
PICNICenhancement
PALplusIC16:9 helper
MEM MEM
HFelectr.
standarddecoder
PICNICenhancement
picturecontrol
audiodemod.
Audioproces.
cableantenna
PAL/NTSC
display
YUV1fh
YUV2fh
RGB2fh
picturecontrol
standarddecoder
PiP+
Mem RGB2fh
CVBS
MEM
100HzFALCON
IC
MEM
MEM
NICAMdecod.
demod
MPEGaudio
MPEGvideo
MEM
chan.decod.
transp.demux
channelbits
Traditional TV sets and
Set-Top Boxes:
• Fixed algorithms for fixed HW architectures
• Upgrade for new services and applications is problematic
• Systems are not flexible
Reinder J. Bril, [email protected]/e Informatica, System Architecture and Networking
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Digital video platform
Bus
VLIWCPU
MIPSCPU
Memory
Coprocessors
Expectations:
• Upgradeable for new servicesand applications
• Fast time-to-market for new features
• Enabling approach for product families
Reinder J. Bril, [email protected]/e Informatica, System Architecture and Networking
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HW Architectures vs. SW Applications
Low-
end
Mid-
range
High-
end
Resources
ProductFamilies
SW-Modules
Algorithm1
Algorithm2
Algorithm4
Algorithm3
Algorithm1 m
in max
Algorithm3
Algorithm2
Algorithm4
Reinder J. Bril, [email protected]/e Informatica, System Architecture and Networking
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Low-
endAlgorithm
1
Algorithm2
Algorithm4
Algorithm3
Algorithm1
Mode 1 Mode 2 Mode 3
Flexibility
Reinder J. Bril, [email protected]/e Informatica, System Architecture and Networking
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Low-
end
Mode 1 Mode 2
Algorithm3
Alg. 4
Algorithm1 Alg. 1
Algorithm3
Scalability
Reinder J. Bril, [email protected]/e Informatica, System Architecture and Networking
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Low-
end
Initial Transitory Final
Algorithm3
Algorithm1 Alg. 1
Algorithm3
Alg. 4
Alg. 1
Algorithm3
Smooth mode transition
Reinder J. Bril, [email protected]/e Informatica, System Architecture and Networking
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Platform constraints
Cost
Functionalitytarget limit
traditionalsystems
scalableapproach
Functionality
Quality
target limit
traditionalsystems
scalableapproach
Reinder J. Bril, [email protected]/e Informatica, System Architecture and Networking
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Platform constraints
• Cost-effectiveness requirement– High volume: low bill of material– Low power– Software solutions are relatively expensive
(mm2 silicon / power)– Average case and worst-case are far apart
Reinder J. Bril, [email protected]/e Informatica, System Architecture and Networking
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Fluctuating resource requirements
time
load
structural load
running average
temporal load
worst-case
Reinder J. Bril, [email protected]/e Informatica, System Architecture and Networking
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Fluctuating resource requirements
• Temporal load changes (very frequent)– from I frame to B frame– more or less motion– transient high peaks
• Structural load changes (less frequent)– scene change– from movie to camera– from news to commercial
Reinder J. Bril, [email protected]/e Informatica, System Architecture and Networking
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Platform constraints
• Cost-effectiveness requirement– High volume: low bill of material– Low power– Software solutions are relatively expensive
(mm2 silicon / power)– Average case and worst-case are far apart
• Conclusion:Aim for average-case resource allocation
Reinder J. Bril, [email protected]/e Informatica, System Architecture and Networking
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High quality video
original
up-scaled
Rendered stream: 60 Hz (TV screen)
Input stream: 24 Hz (movie)
TV companies invest heavily in video enhancement,e.g. temporal up-scaling
Reinder J. Bril, [email protected]/e Informatica, System Architecture and Networking
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High quality video
original
up-scaled
Input stream: 24 Hz (movie)
TV companies invest heavily in video enhancement,e.g. temporal up-scaling
displayed
• Deadline miss leads to “wrong” picture.
• Deadline misses tend to come in bursts (heavy load).
• Valuable work may be lost.
Reinder J. Bril, [email protected]/e Informatica, System Architecture and Networking
22
High quality video
original
up-scaled
Input stream: 24 Hz (movie)
QoS trade-off (at run-time):
Lesser picture quality often better than temporal incorrectness.
TV companies invest heavily in video enhancement,e.g. temporal up-scaling
displayed
Reinder J. Bril, [email protected]/e Informatica, System Architecture and Networking
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High quality video
• QoS = degree of user satisfaction
• User satisfaction has to do with perception:– Lesser picture quality often better than temporal
incorrectness.– Quality fluctuations are perceived as non-quality.– With a scene change, the brain needs some time to re-
focus.– Most people focus on one thing at a time (user focus)– User focus normally is at
• the center of a window,
• the window that received the latest (remote) command.
• Only video specialists can make the necessary trade-offs.
Reinder J. Bril, [email protected]/e Informatica, System Architecture and Networking
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Multimedia Consumer Terminals - Summary
• Media processing from dedicated HW to SW– Flexibility & scalability– Fast time-to-market– Product families
• Platform constraints– Aim for average-case resource allocation
• High quality video– Has real-time requirements;– is about perception -> QoS;– real-time is a QoS parameter;– QoS is primarily an application-domain issue.
Reinder J. Bril, [email protected]/e Informatica, System Architecture and Networking
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Overview
• Multimedia Consumer Terminals• A QoS approach
– Adaptive applications– Budget-based resource manager– Control hierarchy
• Conditionally Guaranteed Budgets• Conclusion
Reinder J. Bril, [email protected]/e Informatica, System Architecture and Networking
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User applications
Media processing
pip
mode 2: main + pip
main
mode 1: main
disk
mode 3: main + pip + disk
Modes
Input Output
DVD
In mode 3, main + pip + disk can not run at highest quality.
Reinder J. Bril, [email protected]/e Informatica, System Architecture and Networking
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disk : non-scalable
main: scalable
mixer : non-scalabledigitizer: non-scalable pip: scalable
hierarchical task
digit
Application execution model (prototype)
DVD dmux
audiodec.
dec.sharpenh.
mixer
audiorend
read
scaler
enc.hwscaler
enc. writer
dec
enc.
scalable task
task
connection to HW IO
buffer
data transferBoth main and pip are scalable.
Reinder J. Bril, [email protected]/e Informatica, System Architecture and Networking
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Scalable Algorithm
FUNCTION 1 FUNCTION 2
FUNCTION 4
FUNCTION 3
QUALITY CONTROL
control signal for
quality level
signal in
signal out
ALGORITHM FOR MEDIA PROCESSING
Quality
Resource needs
Reinder J. Bril, [email protected]/e Informatica, System Architecture and Networking
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s1 s2
DetailFilter
NoiseMeasurement
AmplitudeControl
Filter AC NM
No No No
1D No No
2D No No
2D Yes Yes
QL0
QL1
QL2
QL3
Example: Sharpness Enhancement
Reinder J. Bril, [email protected]/e Informatica, System Architecture and Networking
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Sharpness Enhance.
0 10 20 30Resource needs [MIPS]
Qua
l. es
timat
e
QL0 QL1 QL4
Down-Scaler
0 5 10 15Resource needs [MIPS]
Qua
l. es
timat
eQL0 QL2 QL4
Resource range for SVA examples
Reinder J. Bril, [email protected]/e Informatica, System Architecture and Networking
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Budget-based resource manager
CPU timeapp. 1
time
budget 1
CPU timeapp. 2 budget 2
• Temporal isolation:– Reserved, guaranteed, and enforced budgets
• e.g. 20% of the CPU time every 20 ms;
– Applications run on a “virtual platform”;
Reinder J. Bril, [email protected]/e Informatica, System Architecture and Networking
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Dynamic load (reminder)
• Temporal load changes (very frequent)– from I frame to B frame– more or less motion– transient high peaks
• Structural load changes (less frequent)– scene change– from movie to camera– from news to commercial
• Mode change (infrequent)– functional change– external trigger
Reinder J. Bril, [email protected]/e Informatica, System Architecture and Networking
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Control hierarchy
• Dynamic load at different time-scales:– Temporal load changes;– Structural load changes;– Mode change.
• Layers of control, e.g.– local quality control of applications;– global system utility control.
Reinder J. Bril, [email protected]/e Informatica, System Architecture and Networking
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Adaptive applications
Provide quality levels + estimated resource req.
Co-operative QoS approach
Resource managerProvides guaranteed resource budgets
Local quality control
SVAs…
Global system utility controlOptimizes system utility, sets quality levels + allocates resources
Reinder J. Bril, [email protected]/e Informatica, System Architecture and Networking
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Overview
• Multimedia Consumer Terminals• A QoS approach• Conditionally Guaranteed Budgets
– Why: Resource allocation conflict– How: Extension of QoS approach– Analysis
• Conclusion
Reinder J. Bril, [email protected]/e Informatica, System Architecture and Networking
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Resource requirements (reminder)
time
load
structural load
running average
temporal load
Reinder J. Bril, [email protected]/e Informatica, System Architecture and Networking
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time
load
Resource allocation: worst-case
Not cost-effective
structural load
running average
temporal load
Reinder J. Bril, [email protected]/e Informatica, System Architecture and Networking
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time
load
Resource allocation: close to average
Instantaneous budget increase
Not yet feasible
structural load
running average
temporal load
Reinder J. Bril, [email protected]/e Informatica, System Architecture and Networking
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time
load
Resource allocation: close to average
Instable output quality
Not acceptable forimportant applications
structural load
running average
temporal load
Reinder J. Bril, [email protected]/e Informatica, System Architecture and Networking
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time
load
Resource allocation: close to average
“wasted”
Not cost-effective
structural load
running average
temporal load
Reinder J. Bril, [email protected]/e Informatica, System Architecture and Networking
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Resource allocation conflict
Structural load increase
+close-to-average resource allocation
yields– either instable output quality
not acceptable for important applications– or “wasted” resources
not cost-effective
Reinder J. Bril, [email protected]/e Informatica, System Architecture and Networking
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time
load
Conditionally guaranteed budgets: Why?
Instantaneous budget increase
B
structural load
running average
temporal load
B
Anticipated increase
Reinder J. Bril, [email protected]/e Informatica, System Architecture and Networking
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Conditionally guaranteed budgets: How?
Basic approach (MIA and LIA):– Two modes of quality settings + allocation:
QMIA, BMIA+BMIAQMIA, BMIA
QLIA,N, BLIA +BLIA QLIA,A, BLIA
Anticipated mode(high load for MIA)
Normal mode(low load for MIA)
MIA
LIA
CGB
Reinder J. Bril, [email protected]/e Informatica, System Architecture and Networking
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Conditionally guaranteed budgets: How?
Adaptive applications
Resource manager (RM)
Global system utility control
MIA LIA
Inform MIA, LIA, and RM about both modes
Normal mode
Anticipated mode
Normal mode
Anticipated mode
Normal mode
Anticipated mode
modes
Reinder J. Bril, [email protected]/e Informatica, System Architecture and Networking
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Conditionally guaranteed budgets: How?
Adaptive applications
Resource manager (RM)
Global system utility control
MIANormal mode
Anticipated mode
Normal mode
Anticipated mode
LIANormal mode
Anticipated mode
Running in normal mode
Reinder J. Bril, [email protected]/e Informatica, System Architecture and Networking
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Conditionally guaranteed budgets: How?
MIA detects load increase,
claims BMIA, and switches
mode
Adaptive applications
Resource manager (RM)
Global system utility control
MIANormal mode
Anticipated mode
Normal mode
Anticipated mode
LIANormal mode
Anticipated mode
Claim BMIA
Mode transition
Reinder J. Bril, [email protected]/e Informatica, System Architecture and Networking
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Adaptive applications
Conditionally guaranteed budgets: How?
Resource manager (RM)
Global system utility control
MIANormal mode
Anticipated mode
Normal mode
Anticipated mode
LIANormal mode
Anticipated mode
RM switches mode instantaneously, andinforms LIA
Inform LIA
Mode transition
Reinder J. Bril, [email protected]/e Informatica, System Architecture and Networking
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Adaptive applications
Conditionally guaranteed budgets: How?
Resource manager (RM)
Global system utility control
MIANormal mode
Anticipated mode
Normal mode
Anticipated mode
LIANormal mode
Anticipated mode
LIA switches mode
Running in anticipated mode
Reinder J. Bril, [email protected]/e Informatica, System Architecture and Networking
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Conditionally guaranteed budgets: How?
• Summary basic approach:– Assumption:
• Anticipation of resource needs and modes;
– Allocation phase:• Informing MIA, LIA, and RM about modes;• Delegation of mode changes to MIA;
– Execution phase:• Release and claim of resources by MIA;• Instantaneous mode change by RM.
Reinder J. Bril, [email protected]/e Informatica, System Architecture and Networking
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Conditionally guaranteed budgets: How?
• How to change budgets instantaneously ?• In-the-place-of resource consumption
– LIA consumes BLIA exactly whenMIA would have consumed BMIA
Reinder J. Bril, [email protected]/e Informatica, System Architecture and Networking
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In-the-place-of budget consumption
BMIA BMIA
MIA
LIA
Anticipated mode
Reinder J. Bril, [email protected]/e Informatica, System Architecture and Networking
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In-the-place-of budget consumption
BMIA BMIA
MIA
LIA
Normal mode
Reinder J. Bril, [email protected]/e Informatica, System Architecture and Networking
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In-the-place-of budget consumption
BMIA BMIA
MIA
LIA
Normal mode
Reinder J. Bril, [email protected]/e Informatica, System Architecture and Networking
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In-the-place-of budget consumption
BMIA BMIA
MIA
LIA
Claim BMIA
Mode switch
Reinder J. Bril, [email protected]/e Informatica, System Architecture and Networking
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Conditionally guaranteed budgets
• Analysis
• How to determine BLIA?– Worst-case (i.e. minimal) amount that can be
guaranteed on a periodic basis.
• Cognac-glass algorithm
Reinder J. Bril, [email protected]/e Informatica, System Architecture and Networking
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Cognac-glass algorithm
• How to determine the worst-case BLIA?
MIA
LIA
BMIA BMIA
R
TMIA
TLIA
Reinder J. Bril, [email protected]/e Informatica, System Architecture and Networking
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• How to determine the worst-case BLIA?
• Worst-case for R when BMIA is available:– as early as possible for first overlapping interval;
• “best-case” analysis
– as late as possible for last overlapping interval.• “worst-case” analysis
– based on notion of advancement
• Minimize for all values of R.
Cognac-glass algorithm
Reinder J. Bril, [email protected]/e Informatica, System Architecture and Networking
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Cognac-glass algorithm
• Example– fixed-priority preemptive scheduling– set of four applications
?
MIA
LIA
A2
A1
29
31
14
6
9
-
2
1
7
period budget
Bi BiTi
Reinder J. Bril, [email protected]/e Informatica, System Architecture and Networking
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Advancement
5 10 15 20 25 30
5
10
15
time t
BMIA
BMIA + BMIA
MIA
AMIA(t)
Reinder J. Bril, [email protected]/e Informatica, System Architecture and Networking
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Advancement
5 10 15 20 25 30
5
10
15
time t
BMIA
BMIA + BMIA
WAMIA(t)
Worst-case advancement
Reinder J. Bril, [email protected]/e Informatica, System Architecture and Networking
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Advancement
5 10 15 20 25 30
5
10
15
time t
BMIA
BMIA + BMIA
Worst-case and best-case advancement
WAMIA(t)BAMIA(t)
Reinder J. Bril, [email protected]/e Informatica, System Architecture and Networking
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Situation of worst-case availability
5 15 20 25 30
5
10
15
time t
35 40 45 50 55 60 10
TMIA TMIA
BMIA
BMIA + BMIA
BAMIA(t) WAMIA(t TMIA)
Reinder J. Bril, [email protected]/e Informatica, System Architecture and Networking
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Situation of worst-case availability
5 15 20 25 30
5
10
15
time t
35 40 45 50 55 60 10
TLIA
BMIA
BMIA + BMIA
R
BBMIA(R)
BWMIA(R+TLIATMIA)
Reinder J. Bril, [email protected]/e Informatica, System Architecture and Networking
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Situation of worst-case availability
5
5 15 20 25 30 time t
35 40 45 50 55 60 10
TLIA
BMIA
R
BBMIA(R)
BWMIA(R+TLIATMIA)
BLIA = R
min(BBMIA(R) + BW
MIA(R+ TLIA – TMIA))
Reinder J. Bril, [email protected]/e Informatica, System Architecture and Networking
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Situation of worst-case availability
5
5 15 20 25 30 time t
35 40 45 50 55 60 10
TLIA
BMIA
R
BBMIA(R) BW
MIA(R+TLIA-TMIA)
BLIA = R
min(BBMIA(R) + BW
MIA(R+ TLIA – TMIA))
Reinder J. Bril, [email protected]/e Informatica, System Architecture and Networking
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Situation of worst-case availability
5 15 20 25 30 time t
35 40 45 50 55 60 10
5
TLIA
BMIA
R
The curve looks like the shape of a glass.
Changing the relative phasing R is like tilting the glass…
hence, cognac-glass algorithm.
Reinder J. Bril, [email protected]/e Informatica, System Architecture and Networking
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Situation of worst-case availability
5 15 20 25 30 time t
35 40 45 50 55 60 10
5
TLIA
BMIA
R,lwb
Range for R
Reinder J. Bril, [email protected]/e Informatica, System Architecture and Networking
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Situation of worst-case availability
5 15 20 25 30 time t
35 40 45 50 55 60 10
5
TLIA
BMIA
R,upb
Range for R : [R,lwb, R,upb]
Reinder J. Bril, [email protected]/e Informatica, System Architecture and Networking
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Situation of worst-case availability
5 15 20 25 30 time t
35 40 45 50 55 60 10
5
TLIA
BMIA
R
Range for R
Domination values of R
: [R,lwb, R,upb]
Reinder J. Bril, [email protected]/e Informatica, System Architecture and Networking
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Situation of worst-case availability
5 15 20 25 30 time t
35 40 45 50 55 60 10
5
TLIA
BMIA
R
Range for R
Domination values of R
: [R,lwb, R,upb]
Reinder J. Bril, [email protected]/e Informatica, System Architecture and Networking
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Situation of worst-case availability
5 15 20 25 30 time t
35 40 45 50 55 60 10
5
TLIA
BMIA
R
Range for R
Domination values of R
: [R,lwb, R,upb]
Reinder J. Bril, [email protected]/e Informatica, System Architecture and Networking
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Situation of worst-case availability
5 15 20 25 30 time t
35 40 45 50 55 60 10
5
TLIA
BMIA
R
Range for R
Domination values of R
: [R,lwb, R,upb]
Reinder J. Bril, [email protected]/e Informatica, System Architecture and Networking
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Situation of worst-case availability
5 15 20 25 30 time t
35 40 45 50 55 60 10
5
TLIA
BMIA
R,min = 17
Range for R
Domination values of R
: [R,lwb, R,upb]
BLIA
BLIA = 5
Reinder J. Bril, [email protected]/e Informatica, System Architecture and Networking
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• Summary of the analysis:– Based on notion of advancement;– requires best-case next to worst-case analysis;
– restricted to subset of values for R.
• See [Bril 04] for:– a generalization to arbitrary periods TMIA and TLIA;
– formalization;– efficient calculation.
Cognac-glass algorithm
Reinder J. Bril, [email protected]/e Informatica, System Architecture and Networking
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Overview
• Multimedia Consumer Terminals• A QoS approach• Conditionally Guaranteed Budgets• Conclusion
Reinder J. Bril, [email protected]/e Informatica, System Architecture and Networking
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Conclusion
[Bril 04] R.J. Bril, Real-time scheduling for media processing using conditionally guaranteed budgets, PhD thesis TU/e, IPA Dissertation Series 2004 – 13, Sept. 2004, http://alexandria.tue.nl.extra2/200412419.pdf.
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Acknowledgement
• Research (PhD):– Emile H.L. Aarts (TU/e);
– Gerhard Fohler (Mälardalen University, Sweden);
– Wim F.J. Verhaegh (Philips Research);
– Christian Hentschel (Brandenburger University, Germany);
– Johan J. Lukkien (TU/e);
– Peter D.V. v.d. Stok (TU/e).
• V-QoS program:– All program members and partners;
– Clara M. Otero Pérez;
– Clemens C. Wűst.