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Video On Demand. Video on Demand. One video server Many video data Many clients Client want to watch at any time. Assumptions. Constant bitrate stream Perfect network transport. Unicast Solution. One channel per client No start-up latency No client buffer Low client bandwidth

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Video on demand2 l.jpg
Video on Demand

  • One video server

  • Many video data

  • Many clients

  • Client want to watch at any time

NUS.SOC.CS5248-2010

Roger Zimmermann (based in part on slides by Ooi Wei Tsang)


Assumptions l.jpg
Assumptions

  • Constant bitrate stream

  • Perfect network transport

NUS.SOC.CS5248-2010

Roger Zimmermann (based in part on slides by Ooi Wei Tsang)


Unicast solution l.jpg
Unicast Solution

  • One channel per client

  • No start-up latency

  • No client buffer

  • Low client bandwidth

  • Large server bandwidth

  • Not scalable

NUS.SOC.CS5248-2010

Roger Zimmermann (based in part on slides by Ooi Wei Tsang)


Multicast solution l.jpg
Multicast Solution

  • Batching

    • aggregate client requests

    • serve using multicast

    • clients have to wait

    • No client buffer

    • Low client bandwidth

      “Scheduling Policies for an On-Demand Video Server with Batching”

      Dan, Sitaram, Shahabuddin, IBM

NUS.SOC.CS5248-2010

Roger Zimmermann (based in part on slides by Ooi Wei Tsang)


Multicast solution6 l.jpg
Multicast Solution

  • User-centered approach

    • Scheduling data based on user requests

  • Data-centered approach

    • Don’t care about user

    • Just broadcast popular video

NUS.SOC.CS5248-2010

Roger Zimmermann (based in part on slides by Ooi Wei Tsang)


Multicast solution7 l.jpg
Multicast Solution

  • Batching

  • Staggered Broadcast

NUS.SOC.CS5248-2010

Roger Zimmermann (based in part on slides by Ooi Wei Tsang)


Staggered broadcast l.jpg
Staggered Broadcast

Video

C0

C1

C2

:

NUS.SOC.CS5248-2010

Roger Zimmermann (based in part on slides by Ooi Wei Tsang)


Staggered broadcast9 l.jpg
Staggered Broadcast

  • 2 hour video

  • 5 minutes waiting time

  • Number of channels =

    2 x 60 / 5 = 24

  • Required bandwidth =

1.5Mbps x 24 = 36Mbps

NUS.SOC.CS5248-2010

Roger Zimmermann (based in part on slides by Ooi Wei Tsang)


Multicast solution10 l.jpg
Multicast Solution

  • Batching

  • Staggered Broadcast

    • clients have to wait

    • No client buffer

    • Low client bandwidth

    • Huge server bandwidth

NUS.SOC.CS5248-2010

Roger Zimmermann (based in part on slides by Ooi Wei Tsang)


Multicast solution11 l.jpg
Multicast Solution

  • Batching

  • Staggered Broadcast

  • Periodic Broadcast

NUS.SOC.CS5248-2010

Roger Zimmermann (based in part on slides by Ooi Wei Tsang)


Periodic broadcast l.jpg
Periodic Broadcast

Video

C0

C1

C2

:

NUS.SOC.CS5248-2010

Roger Zimmermann (based in part on slides by Ooi Wei Tsang)


Pyramid broadcast l.jpg
Pyramid Broadcast

Video

C0

C1

C2

:

NUS.SOC.CS5248-2010

Roger Zimmermann (based in part on slides by Ooi Wei Tsang)


Pyramid broadcast14 l.jpg
Pyramid Broadcast

Video

C0

C1

C2

:

NUS.SOC.CS5248-2010

Roger Zimmermann (based in part on slides by Ooi Wei Tsang)


Analysis of pyramid broadcast l.jpg
Analysis of Pyramid Broadcast

  • Notations

    • B : Total available bandwidth

    • Bv : Bandwidth of video

    • Tv : Total length of each video

    • K : Number of segments per video

    • Ti : Length of segment i

    •  : Factor in geometric series

NUS.SOC.CS5248-2010

Roger Zimmermann (based in part on slides by Ooi Wei Tsang)


Channel bandwidth l.jpg
Channel Bandwidth

playback time = Ti

i

i+1

i+1

D’oh!

Just

miss

it!

download time = Ti+1Bv/Bi

Download time for segment i+1 needs

to be smaller than Ti for it to arrive in time.

NUS.SOC.CS5248-2010

Roger Zimmermann (based in part on slides by Ooi Wei Tsang)


Channel bandwidth17 l.jpg
Channel Bandwidth

NUS.SOC.CS5248-2010

Roger Zimmermann (based in part on slides by Ooi Wei Tsang)


Slide18 l.jpg
 = 2

NUS.SOC.CS5248-2010

Roger Zimmermann (based in part on slides by Ooi Wei Tsang)


Start up latency l.jpg
Start-up Latency

  • Worst case waiting time =

NUS.SOC.CS5248-2010

Roger Zimmermann (based in part on slides by Ooi Wei Tsang)


Optimal l.jpg
Optimal

T1

2.5

NUS.SOC.CS5248-2010

Roger Zimmermann (based in part on slides by Ooi Wei Tsang)


Storage requirements l.jpg
Storage Requirements

NUS.SOC.CS5248-2010

Roger Zimmermann (based in part on slides by Ooi Wei Tsang)


Pyramid broadcast22 l.jpg
Pyramid Broadcast

  • Large client bandwidth (KBv)

  • Huge client buffer (70–80% Tv)

NUS.SOC.CS5248-2010

Roger Zimmermann (based in part on slides by Ooi Wei Tsang)


Permutation based pyramid broadcast l.jpg
Permutation-based Pyramid Broadcast

C0

C1

C2

NUS.SOC.CS5248-2010

Roger Zimmermann (based in part on slides by Ooi Wei Tsang)


Channel bandwidth24 l.jpg
Channel Bandwidth

playback time = Ti

i

i+1

i+1

i+1

i+1

D’oh!

Just

miss

it!

download time = Ti+1Bv/Bi

X

X needs to be smaller than Ti for segment

i+1 to arrive in time.

NUS.SOC.CS5248-2010

Roger Zimmermann (based in part on slides by Ooi Wei Tsang)


Channel bandwidth25 l.jpg
Channel Bandwidth

NUS.SOC.CS5248-2010

Roger Zimmermann (based in part on slides by Ooi Wei Tsang)


Client latency l.jpg
Client Latency

NUS.SOC.CS5248-2010

Roger Zimmermann (based in part on slides by Ooi Wei Tsang)


Storage requirement l.jpg
Storage Requirement

  • One channel at a time

  • Can pause and wait

NUS.SOC.CS5248-2010

Roger Zimmermann (based in part on slides by Ooi Wei Tsang)


Storage requirement28 l.jpg
Storage Requirement

pause

k-1

k-1

k

resume

k

Within time X, better

not consume all data

in buffer.

X

NUS.SOC.CS5248-2010

Roger Zimmermann (based in part on slides by Ooi Wei Tsang)


Storage requirement29 l.jpg
Storage Requirement

pause

k-1

k-1

k

k

resume

Within time X, better

not consume all data

in buffer.

X

NUS.SOC.CS5248-2010

Roger Zimmermann (based in part on slides by Ooi Wei Tsang)


Storage requirement30 l.jpg
Storage Requirement

NUS.SOC.CS5248-2010

Roger Zimmermann (based in part on slides by Ooi Wei Tsang)


Comparisons l.jpg
Comparisons

Carter, Long and Paris

“Video on Demand Broadcasting Protocols”

NUS.SOC.CS5248-2010

Roger Zimmermann (based in part on slides by Ooi Wei Tsang)


Slide32 l.jpg

Pyramid Broadcasting

NUS.SOC.CS5248-2010

Roger Zimmermann (based in part on slides by Ooi Wei Tsang)


Skyscraper broadcasting l.jpg
Skyscraper Broadcasting

  • Observations:

    • storage requirement is affected by size of the largest chunk

      So, let’s limit the size of the largest chunk!

NUS.SOC.CS5248-2010

Roger Zimmermann (based in part on slides by Ooi Wei Tsang)


Slide34 l.jpg

Pyramid

Skyscraper

NUS.SOC.CS5248-2010

Roger Zimmermann (based in part on slides by Ooi Wei Tsang)


Skyscraper broadcasting35 l.jpg
Skyscraper Broadcasting

  • Uses series

    1 2 2 5 5 12 12 25 25 52 52 … W W W

NUS.SOC.CS5248-2010

Roger Zimmermann (based in part on slides by Ooi Wei Tsang)


Skyscraper example l.jpg
Skyscraper Example

NUS.SOC.CS5248-2010

Roger Zimmermann (based in part on slides by Ooi Wei Tsang)


Skyscraper example37 l.jpg
Skyscraper Example

NUS.SOC.CS5248-2010

Roger Zimmermann (based in part on slides by Ooi Wei Tsang)


Comparisons38 l.jpg
Comparisons

Carter, Long and Paris

“Video on Demand Broadcasting Protocols”

NUS.SOC.CS5248-2010

Roger Zimmermann (based in part on slides by Ooi Wei Tsang)


Other schemes l.jpg
Other schemes

  • Pagoda Broadcasting1 3 5 15 25 75 125 …

  • Harmonic Broadcasting

    Equal segment size, varies bandwidth instead!

NUS.SOC.CS5248-2010

Roger Zimmermann (based in part on slides by Ooi Wei Tsang)


Multicast solution40 l.jpg
Multicast Solution

  • Batching

  • Staggered Broadcast

  • Periodic Broadcast

    • Sending rate ≥ playback rate

    • May need multiple channels

    • Need additional client buffer

    • Need to wait

NUS.SOC.CS5248-2010

Roger Zimmermann (based in part on slides by Ooi Wei Tsang)


Multicast solution41 l.jpg
Multicast Solution

  • Batching

  • Staggered Broadcast

  • Periodic Broadcast

  • Patching

NUS.SOC.CS5248-2010

Roger Zimmermann (based in part on slides by Ooi Wei Tsang)


Patching l.jpg
Patching

Time

mcast

unicast

Client Request

NUS.SOC.CS5248-2010

Roger Zimmermann (based in part on slides by Ooi Wei Tsang)


Patching43 l.jpg
Patching

Patching Window: W

Time

mcast

mcast

Client Request

NUS.SOC.CS5248-2010

Roger Zimmermann (based in part on slides by Ooi Wei Tsang)


Grace patching l.jpg
Grace Patching

ifW < B

client buffer video[W .. end]

  • 30 minutes video

  • 1 client arrival per minute

  • Total data delivered =

NUS.SOC.CS5248-2010

Roger Zimmermann (based in part on slides by Ooi Wei Tsang)


Scenario 1 b 15mins l.jpg
Scenario 1: B = 15mins

  • 30 minutes video

  • 1 client arrival per minute

  • Total data delivered =

NUS.SOC.CS5248-2010

Roger Zimmermann (based in part on slides by Ooi Wei Tsang)


Scenario 2 b 5mins l.jpg
Scenario 2: B = 5mins

  • 30 minutes video

  • 1 client arrival per minute

  • Total data delivered =

NUS.SOC.CS5248-2010

Roger Zimmermann (based in part on slides by Ooi Wei Tsang)


Scenario 3 b 2mins l.jpg
Scenario 3: B = 2mins

  • 30 minutes video

  • 1 client arrival per minute

  • Total data delivered =

NUS.SOC.CS5248-2010

Roger Zimmermann (based in part on slides by Ooi Wei Tsang)


Summary l.jpg
Summary

  • Batching (User Centered)

  • Staggered Broadcast (Data Centered)

  • Periodic Broadcast (Data Centered)

  • Patching (True VOD)

NUS.SOC.CS5248-2010

Roger Zimmermann (based in part on slides by Ooi Wei Tsang)


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