Building an Adaptive Multimedia System using the Utility Model

Lei Chen, Shahadat Khan, Kin F.Li & Eric G.ManningPANDA Group, University of VictoriaVictoria, British Columbia, Canada

2

Overview

The problem

The Utility Model (UM)

Layered Coding and Transmission (LCT)

How to apply the Utility Model to LCT

The Quality Utility Extension

Unix Kludges

Implementation & Experimental Results

3

The Problem:

How to share resources in a multimedia system?

Contention for resources by competing applications

but

Multimedia real-time constraints demand resource guarantees to guarantee QoS

4

For example ...

Receiver

Bandwidth y

Bandwidth x

Total Bandwidth z

(x+y > z)

File Transfer

Video-on-

demandPlayback

5

Our solution:

apply the Utility Model to Layered Coding and

Transmission

6

We will

Optimize server revenue (utility) while

fully respecting all resource constraints demanded by hard QoS guarantees byon-line session admission & upgrades

devise a bidding HMI protocol

7

The Utility Model (UM)

session utility ui(Qi)

session utility function

system utility objective

resource mapping

system resource constraints

maximize U = ui(Qi) r (Qi) R

session resourcesr (Qi)

gold

session i

bronze silver

Quality Qi

8

The Utility Model (UM)

defines relationships among quality profile, quality-resource mapping, session and system utility, application and system resource constraints,

formulates the Adaptive Multimedia Problem (AMP):

Given:quality-resource mappings and quality-utility

mappings, maximize some system utility function, subject to resource constraints.

9

Knapsack problems:

u=10p=5

u=8p=4

u=15p=8

Pick items to maximize weight (utility) U=u,

subject to volume constraint (resource constraint): p39

10

UM as an MMKP problem

Let: stones be sessions at QoS levels piles of stones be sessions volume be multidimensional (multiple resources):

Choose: at most one stone per pile to maximize revenue (weight) subject to all resource constraints

(multidimensional volume)

11

Solving the AMP:

u=10p=5m=4

u=8p=4m=5

u=15p=8m=7

u=20p=10m=8

u=20p=8

m=10u=25p=15m=15

u=50p=20m=22

u=30p=15m=21

Pick at most one item from each stack in order to maximize U=u,

subject to resource constraints: p39m35

i.e. map AMP to a Multiple-choice Multi-dimensional 0-1 Knapsack Problem (MMKP):

12

UM as an MMKP

Solve the MMKP

• algorithm BBLP gives optimal solutions

• heuristic HEU gives approximate but fast solutions

– 300 sec for moderate problems;– suitable for realtime session admission control

13

Layered coding:

codeword

Base quality improvements

B E1

B: crude image -bronzeB +E1: better - silverB+E1+E2: still better - gold

E1B E2

14

Layered Coding and Transmission

Layered coding methods:

• spatial layering (e.g. JPEG, MPEG, Pyramid coding, Sub-band coding)

• temporal layering (e.g. Motion-JPEG, H.261, DVI, MPEG-2, etc)

15

Layered transmission by multicast:

Send each part of the codeword as a separate multicast group

the more groups received, the better the quality

Layered transmission methods:• IP Multicast and MBone• RLM ( Steve McCanne, UCB)• DSG (Georgia Tech. Inst.)• LVMR (by Xue Li, Georgia Tech.)

16

Using the UM:

Receiver maps quality levels into

resource requirements

UM selects the quality level based on available resources

17

Using the UM:

Receiver

Video-on-DemandPlayback

The Utility Model

Quality selection

bronze

E1

E2

silver

gold

Base

CPU BWin BWout

T

18

Questions

How to design the interface between LCT and the UM?

What resources need to be monitored?

What resources can be monitored?(using an off-the-shelf OS)

What resources can be reserved?

How? (Major Operating Systems problems )

19

More Questions ...

How to derive quality-resource mappings?

How to use the UM in an obsolete* best-effort environment, i.e. the present Internet off-the-shelf operating systems

(Unix, Windows, MacOS)

_____________________* from the viewpoint of multimedia with QoS

20

Demonstrations

best-effort system: the UM adapts by scaling back QoS levels of

the sessions in its domain

reservation based system:all resources & sessions in UM’s domain, so UM optimally sets QoS levels of all

sessions.

21

The Unix QUE

Unix Quality Utility Extension (QUE) provides an extension to a traditional

OS for QoS management

based on the UM

estimates quantities which cannot be easily measured in Unix

22

Unix QUE

implements the concepts of the UM: session profiles, quality-resource mapping, session and system utility, and resource constraints;

supports : admission control and quality adaptation (HMI bidding protocol )

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QUE Components & Interfaces

components:

• Utility Model Engine (UME)

• the OS

• applications

24

QUE Components & Interfaces

Interfaces• The Quality Management Interface(QMI) -

between the UME and applications

• The Graphical User Interface(GUI) - between the UME and users

• The Resource Reservation and Monitoring APIs - between the UME and OS;

25

QUE components:

GUI

Reservation Agent

Resource Monitor

Admission Request or

QoS Mapping Change

Admission Reply or

Quality Change

Reserve get usage

Operating System

Applications

Services Management

QMI

Service API Resource Reservation API Resource Monitoring API

Utility Model Engine

Consume Resources

User

Adaptation Status

QoS Mapping Change

Start Application

Obtain Services

26

QUE: Admission Control (HMI protocol)

UME must guarantee each session’s minimal quality;(by reserving the minimal resources required)

a session is accepted iff• enough free resources to provide minimal QoS, and

• increase in system utility ($$)

sessions must obey UME’s adaptation decisions

27

HMI protocol:Quality Adaptation

occurs when

• new session admitted,• a session’s QoS mappings changes,• a session is terminated,• available resources change.

Operating System

New / Drop / Change session profile

1

13

Utility Model Engine

ApplicationApplication

Application

2

2

Adjust reservation in system resources

Available resources change

Resulting changes in

resource usage

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QoS Mapping

quality-utility mappingrefine the quality-resource mapping:

• quality-methods mapping• method-resources mapping

gold

session i

operating quality Qi

session utility ui(Qi)

session utility function

system utility objective

resource mapping

system resource constraints

bronze silver

maximize U = ui(Qi) constraint r (Qi) R

session resourcer (Qi)

QoS scaling methodmi (Qi)

resource requirementsr (mi)method-resources mapping

quality-methods mapping

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The QUE (cont.)

Example: (gold, silver, bronze)

Video: 5 fps M-JPEGAudio: monoImage: gray scaleConsistency: noneLatency: high

Video: 15 fps VHSAudio: stereoImage: low-res colorConsistency: looseLatency: medium

Video: 30 fps HDTVAudio: surroundImage: hi-res colorConsistency: tightLatency: low

CPU: 30%in BW: 5 Mbpsout BW: 512Kbps

CPU: 20%in BW: 384 Kbpsout BW: 64 Kbps

CPU: 10%in BW: 56 Kbpsout BW: 14.4 Kbps

set_fps(30, HDTV);set_sound(surround);set_img_size(hi_res_c);consis_grp(join_all);...

Method 1

set_fps(15, VHS);set_sound(stereo);set_img_size(lo_res_c);consis_grp(join_base);...

Method 2

set_fps(5, mjpeg);set_sound(mono);set_img_size(grey);consis_grp(none);...

Method 3

User-level QoS

Application-level QoS

System-level QoS

Other Methods

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The QUE (cont.)

QoS Agents: per-session proxy

provides QoS mappings

maintains session profile

handles communication between session and UME.

Admission Reply

Quality Change

Application

$100

Gold

void set_fps (30);

in,out,cpu(30, 15, 25)

$100

Gold

void set_fps (30);

in,out,cpu(30, 15, 25)

$100

Gold

void set_fps (30);

in,out,cpu(30, 15, 25)

QoS Agent

Admission RequestSession Profile

Operating System

Consume Resources

Map Quality-UtilityMap Quality-Methods

Utility Model Engine

Service API

QMI

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OS requirements:

OS must be able to

allocate resources to sessions as decided by QUE

enforce allocations on misbehaving sessions

measure per-session consumption of each resource & report results to QUE

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Meanwhile (in the Unix world) . . .

No enforceable resource allocation available in Unix No per-session resource consumption data System-level monitoring of consumption via /proc Resource consumption estimated as follows:

CPU T = user

_____________________ (% total cpu cycles/sec)user + nice + idle + OS

Tx T = totalTx T - totalTx T-1 (packets / sec )

RxT = totalRx T - totalRx T-1 (packets / sec )

RHS quantities obtainable from /proc in Unix.

33

Estimating resource consumption in unix ...

define:• raw - total amount of a resource provided by the

hardware• manageable - available to the UME• unmanageable - used by applications out of the

UME’s domain– raw = manageable + unmanageable

• allocated - required to support operating QoS of admitted sessions

– free = manageable - allocated : the unused resource

• reserved - required to support minimal QoS of admitted sessions

34

Getting around a unix defect - no reservations:

In an unreserved system (unix)allocations cannot be enforcedapplications contend for resources at run-

time;so manageable resources must be

adjusted to avoid contention but contention cannot be detected at OS

level: (one cannot distinguish full utilization from contention.)

35

Contention Avoidance (the problem):

Only raw T and monitored T are measurable;how to infer manageable T ?

manageable

unmanageable

raw

allocated

free

manageable

monitored

free

raw

Resource usage reading at time tResource partitions in the UME at time t-1

Question: How should the UME partition the resource at time t ?

Quality adaptation result

36

Estimating Manageable for Contention Avoidance:

assume applications do not over-consume

initial condition:manageableT=0 = 95% * rawT=0

Now

monitored T < allocated T => no out-of-domain work => manageable T = 95% * raw T

monitored T > allocated T => out-of-domain work =>

manageable T = raw T - unmanageable T =

raw T - ( monitored T - allocated T-1 )

37

Systems providing resource reservation:

None of the above is necessary

38

Implementation and Results

Prototype implementation

implemented the QUE over Linux implemented VoD, which uses LCT implemented QFTP, a rate controllable

file transfer program

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Experiment setup

QUE used in client

beet.csc.uvic.ca142.104.101.30

Redhat Linux 2.1

Server B

pepper.csc.uvic.ca142.104.101.29

Redhat Linux 2.1

Client C (QUE)

10 Mbps Ethernet

1.6 Mbps 1.6 Mbps

spring.csc.uvic.ca142.104.101.11

Solaris 2.4

Server A

1.6 Mbps 1.6 Mbps1.6 Mbps 1.6 Mbps

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Implementation and Results (cont.)

Best-effort mixed system (like today’s Internet) VoD (in UM’s domain) starts first. FTP (outside UM’s domain) seizes most of the inbound bandwidth. UME required to scale back the quality of VoD VoD customer cancels service agreement, sues provider

Client C

FTP

Utility Model Engine

VoD

Scale back !

contention

Quality Utility Extension

Inbound bandwidth

From Server A

From Server B

41

QUE obeys system and application resource constraints.

QUE: dynamically adjusts manageable resource; adapts application’s QoS to avoid contention; reserves required resources for applications’ minimal QoS; does not scale back beyond the reserved level of the resource.

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

0 10 20 30 40 50 60 70 80 90 100

Re

sou

rce

(In

bo

un

d b

an

dw

idth

)

manageable

allocated

reserved

monitored

A CB

42

Reservation based system (future Internet, modern OS):

VoD preferred over QFTP (more utility offered) preference then changed to favour QFTP (its $$

increased) UME required to optimally adapt both sessions’ QoS

Client C

QFTP

VoD

gold

provision

Quality Utility Extension

Inbound bandwidthsilver

From Server A

From Server B

Quality Resource Utilbronze 40 pps $5silver 60 pps $10gold 120 pps $15

Quality Resource Utilbronze 25 pps $50silver 35 pps $75gold 60 pps $100

Utility Model Engine

silver

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Implementation and Results (cont.)

QUE adapts both applications according to UM decisions:

predictive system behavior

increased system utility

optimal resource allocation among applications

happy customers

0%10%20%30%40%50%60%70%80%90%

100%

0 20 40 60 80 100 120 140 160 180 200 220 240R

eso

urc

e (

Inb

ou

nd

ba

nd

wid

th)

QFTP: allocated

VoD: allocated

A B C D

manageable

$0

$50

$100

$150

$200

$250

0 20 40 60 80 100 120 140 160 180 200 220 240

Sys

tem

Util

ity

A B C D

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Performance

Pentium 166MMX with 40MB memory 300ms (mean) for admission control less than 2ms for quality adaptation

min max avg min max avg3 sessions 0 18 1.09 288 292 290.335 sessions 0 9 1.21 187 292 218.208 sessions 0 45 1.54 292 319 301.7512 sessions 0 11 1.07 293 327 307.50

quality adaptation admission control

45

Summary

The Utility Model: maximizes revenue while fully respecting all QoS guarantees

The application of UM to LCTThe Quality Utility ExtensionKludges to avoid contention in an elderly

OS with no resource reservation Implementation and experimental results