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Multimedia

Oskar Mencer, Stefan R�

ger

oskar@doc.ic.ac.uk • http://www.doc.ic.ac.uk/~oskarOffice: Huxley 422 • Tel: 44-(0207)-594 8268

srueger@doc.ic.ac.uk • http://www.doc.ic.ac.uk/~sruegerOffice: Huxley 379 • Tel: 44-(0207)-594 8355

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Previous Lecture

• MPEG standard: I frames, P frames, etc…

• Chrominance, Luminance, …

• started Multimedia Streaming

=> Quality of Service

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Lecture 12

Creation Processing Compression Transmission----------------------------------------------------------------------------------------------Images The Eye Filters JPEG, GIF, Information

Colours Vision TIFF, PDF Theory----------------------------------------------------------------------------------------------Video Seeing, 2D->3D MPEG, Video Streaming

Motion Summarization RealVideo Peer-to-Peer----------------------------------------------------------------------------------------------Audio The Ear, Filters RealAudio Internet Radio

Sound Surround MP3, MIDI Telephony----------------------------------------------------------------------------------------------

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Video Streaming Technology

Recipe:

- “1 cup” of Networking: some kind of QoS would be good.A reliable network with sufficient throughput capacity.

-“1 cup” of Data Storage: should have sufficiently highMean-Time-To-Failure (MTTF), store many moviesi.e. Terabytes of Data or even Petabytes?In 2003, 1.6 Exabytes of data storage was sold world-wide.

-All this stirred with a set of Protocols to search for and view (stream) a movie.

-Finally, not to be forgotten, Compression on each end to make all this feasible, i.e. MPEG-2.

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Centralised vs. Distributed Systems

What are the advantages and disadvantages of each system?How about for Multimedia distribution?

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Centralised Video-on-Demand (VoD) Server

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Mean-Time-To-Failure (MTTF)

1 Disk has MTTF of 1 M hours.

2 Disks have MTTF of ½ M hours.

n Disks have MTTF of 1/n M hours

Thus, 1000 Disks have MTTF of about 1 month.

Solution: Redundant Arrays of Disks…

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RAID for high MTTF

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VoD Disks / Server ArchitectureVoD slides thanks to Y. Birk

DISK DRIVES

RAM BUFFER STREAMER

NETWORK

CONTROL

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Main Performance Measures & Costs

• Streaming capacity (avg. + guaranteed)

• Response time to viewer requests

• Availability (due to failure mode)

• Overheads• RAM buffer size

Performance Controlable Cost

Must deal with tails of distributions, not onlymean values.

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Data Layout for Max Performance

Problems:

•uncertainty regarding viewing requests

•variable video data rate (e.g., variable-rate compression)

•variable transfer rate (multi-zone recording)

•Inter-disk:

•striping → Load balancing → max perf.

•chunk size: disk utilisation vs. buffer size

•Intra-disk: coping withvariable transfer rate.

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Simplistic Approach: RAID 3

•Simultaneous access to all M disks,BUT, Parity Disk has M times load of others!•Thin stripes•Equivalent to a single fast,

fault-tolerant disk drive ⇒ very convenient

•Chunk size determined by disk efficiency

D D D D D D D D D D P

1 M

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Better: VoD Server on RAID-5

Parity Block holds one parity (XOR) bit for each 4 bit (nibble) on the other 4 disks.If a disk fails, we can recover—as long as we know which one failed.

Streaming Performance Great: Load is distributed evenly!

What is the impact on MTTF for the array?

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VoD Randomized (Irregular) Layouts

• Record chunks on “randomly”-chosen drives.• Benefits: break correlations

• all user scenarios → uniform, "random" load• problems do not persist• load balancing (on average)

• Problem: occasional huge response times at heavy load ⇒large buffers for glitch-prevention.

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VoD Disks Summary

• Many disks => high MTTF • => need redundancy => RAID

• Serve multiple video streams• =>Layout of data is important, but not know in

advance

• => randomize layout of blocks and redundancy.

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Peer-to-Peer Multimedia: e.g. BitTorrent

Bittorrent (bittorrent.com) between centralized & distributed- User runs bitTorrent client. Finds a file and downloads *.torrent- *.torrent tells user about other downloaders,

and a seed (someone who has the whole file)- while downloading, all downloaders share/exchange to

maximise their own download…social model of sharing!

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Peer-to-Peer General Example:(slides thanks to Theo Hong)

•Adaptive content distribution

•Data automatically replicated

•No central point to attack or block

Decentralised peer-to-peer architecture•Global cloud of participants – anyone can join

•Data stored on dynamic subset of nodes•Nodes keep keep information about other nodes

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A self-organising system

•Graph structure self-organises over time•Links evolve as more messages handled

•Nodes start to specialise in clusters•Network dynamically adapts to node failures

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Example for getting a file

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Why does it work?

•The small-world model

•Milgram: six degrees of separation

•Watts: Small Worlds, between order & randomness

•short-distance clustering + long-distance shortcuts

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Summary

• Quality of Service: latency and throughput guarantees

• Distributed versus Centralised Systems

• VoD Technology versus Peer-to-Peer RAID, Randomisation, BitTorrent, …