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Lecture 14: Distributed Multimedia Systems Haibin Zhu, PhD. Assistant Professor Department of Computer Science Nipissing University © 2002
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Lecture 14: Distributed Multimedia Systems Haibin Zhu, PhD. Assistant Professor Department of Computer Science Nipissing University © 2002.

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Page 1: Lecture 14: Distributed Multimedia Systems Haibin Zhu, PhD. Assistant Professor Department of Computer Science Nipissing University © 2002.

Lecture 14:Distributed Multimedia Systems

Haibin Zhu, PhD.

Assistant Professor

Department of Computer Science

Nipissing University

© 2002

Page 2: Lecture 14: Distributed Multimedia Systems Haibin Zhu, PhD. Assistant Professor Department of Computer Science Nipissing University © 2002.

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Contents

Introduction Characteristics of multimedia data Quality of service management Resource management Stream adaptation Summary

Page 3: Lecture 14: Distributed Multimedia Systems Haibin Zhu, PhD. Assistant Professor Department of Computer Science Nipissing University © 2002.

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Learning objectives

To understand the nature of multimedia data and the scheduling and resource issues associated with it.

To become familiar with the components and design of distributed multimedia applications.

To understand the nature of quality of service and the system support that it requires.

To explore the design of a state-of-the-art, scalable video file service; illustrating a radically novel design approach for quality of service.

*

Page 4: Lecture 14: Distributed Multimedia Systems Haibin Zhu, PhD. Assistant Professor Department of Computer Science Nipissing University © 2002.

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A distributed multimedia system

Wide area gateway Videoserver

DigitalTV/radioserver

Video cameraand mike

Local network Local network

Figure 15.1

Applications:– non-interactive: net radio and TV, video-on-demand, e-learning, ...

– interactive: voice &video conference, interactive TV, tele-medicine, multi-user games, live music, ...

*

Page 5: Lecture 14: Distributed Multimedia Systems Haibin Zhu, PhD. Assistant Professor Department of Computer Science Nipissing University © 2002.

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Multimedia in a mobile environment

Applications:– Emergency response systems, mobile commerce, phone service,

entertainment, games, ...

*

Global System for Mobile Communications

Page 6: Lecture 14: Distributed Multimedia Systems Haibin Zhu, PhD. Assistant Professor Department of Computer Science Nipissing University © 2002.

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Characteristics of multimedia applications

Large quantities of continuous data Timely and smooth delivery is critical

– deadlines– throughput and response time guarantees

Interactive MM applications require low round-trip delays Need to co-exist with other applications

– must not hog resources

Reconfiguration is a common occurrence– varying resource requirements

Resources required:– Processor cycles in workstations – and servers– Network bandwidth (+ latency)– Dedicated memory– Disk bandwidth (for stored media)

At the right timeand in the right quantities

*

Page 7: Lecture 14: Distributed Multimedia Systems Haibin Zhu, PhD. Assistant Professor Department of Computer Science Nipissing University © 2002.

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Application requirements

Network phone and audio conferencing– relatively low bandwidth (~ 64 Kbits/sec), but delay times must be short ( <

250 ms round-trip)

Video on demand services– High bandwidth (~ 10 Mbits/s), critical deadlines, latency not critical

Simple video conference– Many high-bandwidth streams to each node (~1.5 Mbits/s each), high

bandwidth, low latency ( < 100 ms round-trip), synchronised states.

Music rehearsal and performance facility– high bandwidth (~1.4 Mbits/s), very low latency (< 100 ms round trip), highly

synchronised media (sound and video < 50 ms).

*

http://www.topsavings.net/dedicated-t-1.html

Page 8: Lecture 14: Distributed Multimedia Systems Haibin Zhu, PhD. Assistant Professor Department of Computer Science Nipissing University © 2002.

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System support issues and requirements

Scheduling and resource allocation in most current OS’s divides the resources equally amongst all comers (processes)– no limit on load

– can’t guarantee throughput or response time

MM and other time-critical applications require resource allocation and scheduling to meet deadlines– Quality of Service (QoS) management

Admission control: controls demand QoS negotiation: enables applications to negotiate admission

andreconfigurations

Resource management: guarantees availability of resources for admitted applications

– real-time processor and other resource scheduling

*

Page 9: Lecture 14: Distributed Multimedia Systems Haibin Zhu, PhD. Assistant Professor Department of Computer Science Nipissing University © 2002.

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Characteristics of typical multimedia streams

Data rate(approximate)

Sample or frame frequency size

Telephone speech 64 kbps 8 bits 8000/secCD-quality sound 1.4 Mbps 16 bits 44,000/secStandard TV video(uncompressed)

120 Mbps up to 640 x 480pixels x 16 bits

24/sec

Standard TV video (MPEG-1 compressed)

1.5 Mbps variable 24/sec

HDTV video(uncompressed)

1000–3000 Mbps up to 1920 x 1080pixels x 24 bits

24–60/sec

HDTV video and DVDMPEG-2 compressed)

10–30 Mbps variable 24–60/sec

Figure 15.3

*

Page 10: Lecture 14: Distributed Multimedia Systems Haibin Zhu, PhD. Assistant Professor Department of Computer Science Nipissing University © 2002.

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Typical infrastructure components for multimedia applications

Microphones

Camera

Screen

Window system

CodecD

BMixer

PC/workstation PC/workstation

C Videostore

Networkconnections

K

L

M

CodecA G

CodecH

Windowsystem

Video file system

: multimedia stream

White boxes represent media processing components, many of which are implemented in software, including:

codec: coding/decoding filtermixer: sound-mixing component

*

Figures 15.4 & 15.5

Component Bandwidth Latency Loss rate Resources required

Camera Out: 10 frames/sec, raw video640x480x16 bits

Zero

A Codec In:Out:

10 frames/sec, raw videoMPEG-1 stream

Interactive Low 10 ms CPU each 100 ms;10 Mbytes RAM

B Mixer In:Out:

2 44 kbps audio1 44 kbps audio

Interactive Very low 1 ms CPU each 100 ms;1 Mbytes RAM

H Windowsystem

In:Out:

various50 frame/sec framebuffer

Interactive Low 5 ms CPU each 100 ms; 5 Mbytes RAM

K Networkconnection

In/Out: MPEG-1 stream, approx.1.5 Mbps

Interactive Low 1.5 Mbps, low-lossstream protocol

L Networkconnection

In/Out: Audio 44 kbps Interactive Very low 44 kbps, very low-lossstream protocol

This application involves multiple concurrent processes in the PCs

Other applications may also be running concurrently on the same computers

They all share processing and network resources

Page 11: Lecture 14: Distributed Multimedia Systems Haibin Zhu, PhD. Assistant Professor Department of Computer Science Nipissing University © 2002.

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Quality of service management

Allocate resources to application processes – according to their needs in order to achieve the desired quality of multimedia

delivery

Scheduling and resource allocation in most current OS’s divides the resources equally amongst all processes– no limit on load

– can’t guarantee throughput or response time

*

Page 12: Lecture 14: Distributed Multimedia Systems Haibin Zhu, PhD. Assistant Professor Department of Computer Science Nipissing University © 2002.

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Elements of Quality of Service (QoS) management

Admission control: controls demand

QoS negotiation: enables applications to negotiate admission and

reconfigurations

Resource management: guarantees availability of resources for

admitted applications

real-time processor and other resource scheduling

Page 13: Lecture 14: Distributed Multimedia Systems Haibin Zhu, PhD. Assistant Professor Department of Computer Science Nipissing University © 2002.

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Figure 15.5QoS specifications for components of the application shown in Figure 15.4

Component Bandwidth Latency Loss rate Resources required

Camera Out: 10 frames/sec, raw video640x480x16 bits

Zero

A Codec In:Out:

10 frames/sec, raw videoMPEG-1 stream

Interactive Low 10 ms CPU each 100 ms;10 Mbytes RAM

B Mixer In:Out:

2 44 kbps audio1 44 kbps audio

Interactive Very low 1 ms CPU each 100 ms;1 Mbytes RAM

H Windowsystem

In:Out:

various50 frame/sec framebuffer

Interactive Low 5 ms CPU each 100 ms; 5 Mbytes RAM

K Networkconnection

In/Out: MPEG-1 stream, approx.1.5 Mbps

Interactive Low 1.5 Mbps, low-lossstream protocol

L Networkconnection

In/Out: Audio 44 kbps Interactive Very low 44 kbps, very low-lossstream protocol

Page 14: Lecture 14: Distributed Multimedia Systems Haibin Zhu, PhD. Assistant Professor Department of Computer Science Nipissing University © 2002.

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The QoS manager’s task

Application components specify their QoS requirements to QoS manager

Yes No

Yes No

Flow spec.

Resource contract

Admission control QoS negotiation

QoS manager evaluates new requirementsagainst the available resources.

Sufficient?

Reserve the requested resources

Allow application to proceed

Application runs with resources as per resource contract

Negotiate reduced resource provision with application.Agreement?

Do not allow application to proceed

Application notifies QoS manager of increased resource requirements

*

Figure 15.6

*

Page 15: Lecture 14: Distributed Multimedia Systems Haibin Zhu, PhD. Assistant Professor Department of Computer Science Nipissing University © 2002.

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QoS Parameters

Bandwidth– rate of flow of multimedia data

Latency– time required for the end-to-end transmission of a single data element

Jitter variation in latency :– dL/dt

Loss rate– the proportion of data elements that can be dropped or delivered late

*

Page 16: Lecture 14: Distributed Multimedia Systems Haibin Zhu, PhD. Assistant Professor Department of Computer Science Nipissing University © 2002.

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Managing the flow of multimedia data

Flows are variable– video compression methods such as MPEG (1-4) are based on

similarities between consecutive frames – can produce large variations in data rate

Burstiness– Linear bounded arrival process (LBAP) model:

maximum flow per interval t = Rt + B (R = average rate, B = max. burst)

– buffer requirements are determined by burstiness– Latency and jitter are affected (buffers introduce additional delays)

Traffic shaping– method for scheduling the way a buffer is emptied

*

Page 17: Lecture 14: Distributed Multimedia Systems Haibin Zhu, PhD. Assistant Professor Department of Computer Science Nipissing University © 2002.

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Protocol version

Maximum transmission unit

Token bucket rate

Token bucket size

Maximum transmission rate

Minimum delay noticed

Maximum delay variation

Loss sensitivity

Burst loss sensitivity

Loss interval

Quality of guarantee

Bandwidth:

Delay:

Loss:

Figure 15.8 The RFC 1363 Flow Spec

acceptable jitter

acceptable latency

maximum rate

burstiness

percentage per T

maximum consec-utive loss

T

value

50Mbps

150ms

<1/1000

Page 18: Lecture 14: Distributed Multimedia Systems Haibin Zhu, PhD. Assistant Professor Department of Computer Science Nipissing University © 2002.

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(a) Leaky bucket

*

Figure 15.7

process 1

process 2

Traffic shaping algorithms – leaky bucket algorithm

analogue of leaky bucket:– process 1 places data into a buffer in bursts– process 2 in scheduled to remove data regularly in smaller amounts– size of buffer, B determines:

maximum permissible burst without loss maximum delay

Page 19: Lecture 14: Distributed Multimedia Systems Haibin Zhu, PhD. Assistant Professor Department of Computer Science Nipissing University © 2002.

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Token generator

(b) Token bucket

*

Figure 15.7

Traffic shaping algorithms – token bucket algorithm

Implements LBAP– process 1 delivers data in bursts– process 2 generates tokens at a fixed rate– process 3 receives tokens and exploits them to deliver output as quickly as it gets

data from process 1

Result: bursts in output can occur when some tokens have accumulated

process 2 process 1

process 3

tokens: permits to place x bytes into output buffer

Page 20: Lecture 14: Distributed Multimedia Systems Haibin Zhu, PhD. Assistant Professor Department of Computer Science Nipissing University © 2002.

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Admission control

Admission control delivers a contract to the application guaranteeing:For each computer:

cpu time, available at specific intervals memory

Before admission, it must assess resource requirements and reserve them for the application

– Flow specs provide some information for admission control, but not all - assessment procedures are needed

– there is an optimisation problem: clients don't use all of the resources that they requested flow specs may permit a range of qualities

– Admission controller must negotiate with applications to produce an acceptable result

For each network connection:bandwidthlatency

For disks, etc.:bandwifthlatency

*

Page 21: Lecture 14: Distributed Multimedia Systems Haibin Zhu, PhD. Assistant Professor Department of Computer Science Nipissing University © 2002.

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Resource management

Scheduling of resources to meet the existing guarantees:Fair scheduling allows all processes some portion of the resources based on

fairness: E.g. round-robin scheduling (equal turns), fair queuing (keep queue lengths equal) not appropriate for real-time MM because there are deadlines for the delivery of

data

Real-time scheduling traditionally used in special OS for system control applications - e.g. avionics. RT schedulers must ensure that tasks are completed by a scheduled time.

Real-time MM requires real-time scheduling with very frequent deadlines.

Suitable types of scheduling are:

Earliest deadline first (EDF)

Rate-monotonic

e.g. for each computer:cpu time, available at specific intervalsmemory

*

Page 22: Lecture 14: Distributed Multimedia Systems Haibin Zhu, PhD. Assistant Professor Department of Computer Science Nipissing University © 2002.

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EDF(Earliest Deadline First) schedulingEach task specifies a deadline T and CPU seconds S to the scheduler for each work item (e.g. video frame). EDF scheduler schedules the task to run at least S seconds before T (and pre-empts it after S if it hasn't yielded).It has been shown that EDF will find a schedule that meets the deadlines, if one exists. (But for MM, S is likely to be a millisecond or so, and there is a danger that the scheduler may have to run so frequently that it hogs the cpu).

Rate-monotonic scheduling assigns priorities to tasks according to their rate of data throughput (or workload). Uses less CPU for scheduling decisions. Has been shown to work well where total workload is < 69% of CPU.

Page 23: Lecture 14: Distributed Multimedia Systems Haibin Zhu, PhD. Assistant Professor Department of Computer Science Nipissing University © 2002.

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Stream adaptation: Scaling and filtering

SourceTargets

High bandwidth

Medium bandwidth

Low bandwidth

*

Figure 15.9

Scaling reduces flow rate at source– temporal: skip frames or audio samples– spatial: reduce frame size or audio sample quality

Filtering reduces flow at intermediate points– RSVP is a QoS negotiation protocol that negotiates the rate at each intermediate node,

working from targets to the source.

The Principle of BitTorrent (http://download.bitcomet.com/doc/principle.htm)

Page 24: Lecture 14: Distributed Multimedia Systems Haibin Zhu, PhD. Assistant Professor Department of Computer Science Nipissing University © 2002.

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QoS and the Internet

Very little QoS in the Internet at present– New protocols to support QoS have been developed, but their implementation

raises some difficult issues about the management of resources in the Internet.

RSVP(http://www.isi.edu/div7/rsvp/rsvp.html)– Network resource reservation

– Doesn’t ensure enforcement of reservations

RTP (http://www.cs.columbia.edu/~hgs/rtp/)– Real time data transmission over IP

need to avoid adding undesirable complexity to the Internet

IPv6 has some hooks for it

Page 25: Lecture 14: Distributed Multimedia Systems Haibin Zhu, PhD. Assistant Professor Department of Computer Science Nipissing University © 2002.

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Page 26: Lecture 14: Distributed Multimedia Systems Haibin Zhu, PhD. Assistant Professor Department of Computer Science Nipissing University © 2002.

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Video conferencing

Video conferencing applications can also support:– Text chat– Document sharing (exchanging files)– PowerPoint– Application sharing (running the same program, viewing at the same

content)

frequently there is a way for any participant to control the program– Electronic white board – everyone can view what

someone writes and draws

The word “Collaboration” appears a lot in docs

Page 27: Lecture 14: Distributed Multimedia Systems Haibin Zhu, PhD. Assistant Professor Department of Computer Science Nipissing University © 2002.

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Video conferencing

Desktop (computer) videoconferencing can be donethrough applications such as– Netmeeting (Windows 2000 and XP)

–http://www.microsoft.com/windows/netmeeting/– Windows Messenger (Windows XP)

–http://www.microsoft.com/windowsxp/windowsmessenger/– MSN Messenger (Windows) - http://messenger.msn.com/iChat

(Apple) - http://www.apple.com/ichat/

Page 28: Lecture 14: Distributed Multimedia Systems Haibin Zhu, PhD. Assistant Professor Department of Computer Science Nipissing University © 2002.

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Video conferencing

the clients we have mentioned are mainly used for “Instant Messaging”

IM is an exchange of text between two or more people who are online at the same time

supports group interaction

a conversation by typing instead of speaking

this is great for short conversations but doesn’t support extended discussion well

moving from text to audio and video makes the interaction much more natural

Page 29: Lecture 14: Distributed Multimedia Systems Haibin Zhu, PhD. Assistant Professor Department of Computer Science Nipissing University © 2002.

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Page 30: Lecture 14: Distributed Multimedia Systems Haibin Zhu, PhD. Assistant Professor Department of Computer Science Nipissing University © 2002.

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Video conferencing

Can buy videoconferencing appliances that plug into your computer. They come with:– camera– microphone– speaker– encoding of video and audio streams done in hardware– software to drive it all

load on your PC for encoding is then quite small

Page 31: Lecture 14: Distributed Multimedia Systems Haibin Zhu, PhD. Assistant Professor Department of Computer Science Nipissing University © 2002.

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Video conferencing

Video conferencing is a technology in which video and audio streams are transmitted among the various geographically separated participants in a meeting.

Typically this is done through a room which has been set up by a telephone company

booking the room also books an operator from the phone company to run the meeting for you

Page 32: Lecture 14: Distributed Multimedia Systems Haibin Zhu, PhD. Assistant Professor Department of Computer Science Nipissing University © 2002.

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Summary

MM applications and systems require new system mechanisms to handle large volumes of time-dependent data in real time (media streams).

The most important mechanism is QoS management, which includes resource negotiation, admission control, resource reservation and resource management.

Negotiation and admission control ensure that resources are not over-allocated, resource management ensures that admitted tasks receive the resources they were allocated.

Video conferences