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PLANETE project presentation:. Scalable video distribution techniques. Laurentiu Barza. Sophia Antipolis 12 October 2000. Motivation. User behaviour: skewed access: Zipf Rule 20/80 desire rapid access may be willing to sacrifice access time and some interactivity for lower cost service

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Scalable video distribution techniques l.jpg

PLANETE project presentation:

Scalable video distribution techniques

Laurentiu Barza

Sophia Antipolis 12 October 2000


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Motivation

  • User behaviour:

    • skewed access: Zipf Rule 20/80

    • desire rapid access

    • may be willing to sacrifice access time and some interactivity for lower cost service

  • Goal: scalable service that provides almost « true VoD » at a much lower cost


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Outline

Basic schemes:

  • Server-Push Broadcast

    - Baseline

    - DeBey

    - Pyramid & Skyscraper

    - Tailor-Made

  • Client-Pull with Multicast

    - Batching


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Baseline Broadcast Scheme

  • Continuos multicast of hot videos

  • M videos

  • K channels

  • assign K/M channels to each video

  • schedule video start times

  • « pay-per-view » model


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Baseline Broadcast

Length of Movie

3 channels/movie


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DeBey Broadcast

  • Split a video into N equal sized segments

  • Segment “m” is transmitted ONCE every “m” time

  • reduce the mean transmission rate

  • peak transmission rate very high


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De Bey Broadcast

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Pyramid broadcasting

  • Split video into N segments of lengths L1,L2,…,Ln

  • L = L1+L2+…+Ln

  • Segment size: Li =  * Li+1

  • lower max access time than baseline scheme

  • the client has to listen 2 channels simultaneous

  • significant receiver buffering: up to 70% of video length


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Pyramid Segmentation

Skyscraper segmentation


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Skyscraper Broadcasting

  • use relative segment size progression: 1, 2, 2, 5, 5, 12, 12, 25, 25, 52, 52…

  • requires less buffering than pyramid scheme

  • requires strict synchronization among the multicast channels


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Tailor-Made approach

  • Cover all possible design dimensions

    • server transmission rate

    • start-up latency

    • peak client recording rate

    • peak client storage requirements

  • Is a modification of de Bey:

    • all the segments have the same length but are transmitted continuously


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Taylor-Made Approach

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Taylor-Made Approach

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Partial conclusion

Proposed schemes characteristics:

  • are server-push approach

  • are designed for hot video

  • vary the way they segment a video

  • trade-off server transmission rate, client IO bandwidth and client storage and recording requirements

  • have all non-zero start-up latency


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Client-pull: Batching

  • delay request for a video until a certain number of requests for that video arrive before the video is delivered

  • batching is only effective for popular videos

  • reduce server and network resource requirements

  • start-up latency can be very high

    • popularity of required video

    • no. Of requests required to schedule a video


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Controlled multicast

  • Controlled Multicast = Batching + Optimal Patching

  • define a patch threshold that trades off the size of the patches and the frequency in which new multicast channels are initiated


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Catching

  • Server broadcast video via dedicated multicast channels

  • Client

    • immediately joins the appropriate multicast channel

    • requests to the server the missing first part of the video

  • Server sends the first part to the client via a dedicated unicast channel


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Multicast with caching (Mcache)

  • Server multicasts body of a video using

    • object channels: multicast the body of the video

    • patch channels: multicast parts of the video right after the prefix

  • Client initiates two parallel requests

    • the prefix from the cache

    • video body from the server

  • Server:calculates schedule and inform client which channel and when to join


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Conclusion

Various schemes for scalable video distribution

  • Concern only hot and popular video

  • Emulate the native Video on Demand service while requiring much less ressources at the server

  • Server Push vs. Client Pull models

  • Zero latency vs. Non-zero latency schemes


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patched

Prefix(cached)

Body(server)


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