DistributedSystem Multimedia

Distributed Multimedia Systems

THOAI NAM

Faculty of Computer Science and Engineering

HCMC University of Technology

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Faculty of Computer Science and Engineering - HCMUT

Multimedia applications

Video conf, digital TV, VoIP

Real-time

Video/audio data as continuous and time-based

Shared resources in Internet

Quality of service (QoS)

Quality of service management

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Figure 20.1, Coulouris, Dollimore, Kindberg and Blair, Distributed Systems: Concepts and Design Edn. 5 Pearson Education 2012

A distributed multimedia system

Faculty of Computer Science and Engineering - HCMUT -1.3-

Characteristics of typical multimedia streams

Data rate

(approximate)

Sample or frame

size frequency

Telephone speech 64 kbps 8 bits 8000/sec

CD-quality sound 1.4 Mbps 16 bits 44,000/sec

Standard TV video

(uncompressed)

120 Mbps up to 640 x 480

pixels x 16 bits

24/sec

Standard TV video

(MPEG-1 compressed)

1.5 Mbps variable 24/sec

HDTV video

(uncompressed)

10003000 Mbps up to 1920 x 1080 pixels x 24 bits

2460/sec

HDTV video

MPEG-2 compressed)

1030 Mbps variable 2460/sec




QoS-less applications

Deployed in QoS-less, best-effort computing and network environment

Web-based multimedia Access to streams of audio and video published via the web: best-effort

quality

Not guarantee of performance

Youtube, Hulu and BBC iPlayer

Video-on-demand services Video sent from the sources to the end users

Buffer used

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Highly interactive applications

Internet telephony, video conference, a music rehearsal & performance facility enabling musicians at different locations to perform in an ensemble

Requirements: Low-latency communication

Synchronous distributed state

Media synchronization

External synchronization

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Typical infrastructure components for multimedia applications



QoS specifications for components of applications in Fig 20.3

Component Bandwidth Latency Loss rate Resources required

Camera Out: 10 frames/sec, raw video

640x480x16 bits

Zero

A Codec In:

Out:

10 frames/sec, raw video

MPEG-1 stream

Interactive Low 10 ms CPU each 100 ms;

10 Mbytes RAM

B Mixer In:

Out:

2 x 44 kbps audio

1 x 44 kbps audio

Interactive Very low 1 ms CPU each 100 ms;

1 Mbytes RAM

H Window

system

In:

Out:

various

50 frame/sec framebuffer

Interactive Low 5 ms CPU each 100 ms;

5 Mbytes RAM

K Network

connection

In/Out: MPEG-1 stream, approx.

1.5 Mbps

Interactive Low 1.5 Mbps, low-loss

stream protocol

L Network

connection

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

stream protocol




QoS management

Multimedia applications compete for resources In computers: processor cycles, bus cycles, buffer capacity

In the networks: physical transmission links, switches, gateways

Current solutions: Round-robin or other scheduling scheme that shares the processing

resources on a best-effort basis among all of the tasks currently competing for the central processor

Ethernet: manages a shared transmission medium in a best-effort manner. Collisions are likely to occur when the network is heavily loaded, and this scheme cannot provide any guarantees regarding the bandwidth or latency in such situations

The management and allocation of resources to provide such guarantees is referred to as quality of service management

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The QoS managers task




Quality of service negotiation

Bandwidth

The bandwidth of a multimedia stream or component is the rate at which data flows through it

Latency Latency is the time required for an individual data element to move

through a stream from the source to the destination

Loss rate Some apps accept a certain rate of data loss i.e., dropped video frames or

audio samples

The acceptable ratios are usually kept low seldom more than 1% and much lower for quality-critical applications.

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Burstiness

Consider three streams of 1 Mbps:

One stream transfers a single frame of 1 Mbit every second

The second is an asynchronous stream of computer-generated animation elements with an average bandwidth of 1 Mbps

The third sends a 100-bit sound sample every microsecond.

Whereas all three streams require the same bandwidth, their traffic patterns are very different

The burst parameter specifies the maximum number of media elements that may arrive early That is, before they should arrive according to the regular arrival rate

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Model of linear-bounded arrival processes(LBAP)

The model of linear-bounded arrival processes (LBAP) used in Anderson [1993] defines the maximum number of messages in a stream during any time interval t as Rt+ B, where R is the rate and B is the maximum size of burst

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Traffic shaping algorithms

Token generator

(a) Leaky bucket (b) Token bucket




The leaky bucket algorithm

Any stream can be regulated by inserting a buffer at the source and by defining a method by which data elements leave the buffer

The bucket can be filled arbitrarily with water until it is full; through a leak at the bottom of the bucket water will flow continuously

ensures that a stream will never flow with a rate higher than R. The size of the buffer B defines the maximum burst a stream can incur without losing elements. B also bounds the time for which an element will remain in the bucket

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The token bucket algorithm

The leaky bucket algorithm completely eliminates bursts. Such elimination is not always necessary as long as bandwidth is bounded over any time interval.

The token bucket algorithm achieves this while allowing larger bursts to occur when a stream has been idle for a while

Data are generated at a fixed rate, R. They are collected in a bucket of size B

Data of size S can be sent only if at least S tokens are in the bucket. The send process then removes these S tokens

ensures that over any interval t the amount of data sent is not larger than Rt+ B

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The RFC 1363 Flow Spec (1)

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:




The RFC 1363 Flow Spec (2)

The maximum transmission unit and maximum transmission rate determine the maximum bandwidth required by the stream

The token bucket size and rate determine the burstiness of the stream

The delay characteristics are specified by the minimum delay that an application can notice (since we wish to avoid over optimization for short delays) and the maximum jitter it can accept

The loss characteristics are defined by the total number of losses acceptable over a certain interval and the maximum number of consecutive losses acceptable

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Resource management

Fair scheduling Round-robin scheduling to all streams in the same class

Fair queuing: packet-by-packet, bit-per-bit

Weighted fair queuing

Real-time scheduling Traditional real-time scheduling methods suit the model of regular

continuous multimedia streams very well

EDF scheduler uses a deadline that is associated with each of its work items to determine the next item to be processed: the item with the earliest deadline goes first

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Stream adaption (1)

Scaling: adapt a stream to the bandwidth available in the system before it enters a bottleneck resource in order to resolve contention

Temporal scaling: Reduces the resolution of the video stream in the time domain by decreasing the number of video frames transmitted within an interval

Spatial scaling: Reduces the number of pixels of each image in a video stream

Frequency scaling: Modifies the compression algorithm applied to an image

Amplitudinal scaling: Reduces the colour depths for each image pixel

Colour-space scaling: Reduces the number of entries in the colour space. One way to realize colour-space scaling is to switch from colour to greyscale presentation

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Stream adaption (2)

Filtering As scaling modifies a stream at the source, it is not always suitable for

applications that involve several receivers

Filtering is a method that provides the best possible QoS to each target by applying scaling at each relevant node on the path from the source to the target

RSVP [Zhang et al. 1993] is an example of a QoS negotiation protocol that supports filtering

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Filtering

Source Targets

High bandwidth

Medium bandwidth

Low bandwidth




The Tiger video file server

Tiger video file server developed at the Microsoft Research Labs [Bolosky et al.1996]

Video-on-demand for a large number of users

Quality of service Video streams must be supplied at a constant rate with a maximum jitter that is determined by the (assumed small) amount of buffering available at the clients and a very low loss rate

Scalable and distributed: 10.000 clients

Low-cost hardware

Fault tolerance

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Tiger video file server hardware configuration

Controller

Cub 0 Cub 1 Cub 2 Cub 3 Cub n

ATM switching network

video distribution to clients

Start/Stop requests from clients

low-bandwidth network

high-bandwidth

0 n+1 1 n+2 2 n+3 n+4 n 2n+1 3



Tiger schedule

0 1 2

slot 0

viewer 4

slot 1

free

slot 2

free

slot 3

viewer 0

slot 4

viewer 3

slot 5

viewer 2

slot 6

free

slot 7

viewer 1

block play time T

block service

time t

state state state state state




BitTorrent

BitTorrent [www.bittorrent.com] is a popular peer-to-peer file-sharing application designed particularly for downloading large files (including video files)

Splitting of files into fixed-sized chunks and the subsequent availability of chunks at various sites across the peer-to-peer network

Clients can then download a number of chunks in parallel from different sites

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A .torrent file

The name and length of the file

The location of a tracker(specified as a URL), which is a centralized server that manages downloads of that particular file

A checksum associated with each chunk, generated using the SHA-1 hashing algorithm, that enables content to be verified following download

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The incentive mechanism

The tit-for-tat mechanism [Cohen 2003]

Preference to downloading peers who have previously or who are currently uploading to that site

Peers to behave as good citizens

A given peer supports downloading from n simultaneous peers by unchoking these peers

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BitTorrent Terminology



End System Multicast: an approach to real-time video streaming



An example tree in ESM



DistributedSystem Multimedia

Documents

mbps interactive low

distributed systems

video conference

stream interactive low

sec hdtv video mpeg

raw video mpeg

sec hdtv video uncompressed

sec standard tv video