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Can Internet Video-on-Demand Be Profitable?. Cheng Huang, Jin Li (Microsoft Research), Keith W. Ross (Polytechnic University) ACM SIGCOMM 2007. Outlines. Motivation Trace – User demand & behavior Peer assisted VoD Theory Real-trace-driven simulation Cross ISP traffic issue Conclusion.

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can internet video on demand be profitable

Can Internet Video-on-Demand Be Profitable?

Cheng Huang, Jin Li (Microsoft Research), Keith W. Ross (Polytechnic University)

ACM SIGCOMM 2007

outlines
Outlines
  • Motivation
  • Trace – User demand & behavior
  • Peer assisted VoD
    • Theory
    • Real-trace-driven simulation
  • Cross ISP traffic issue
  • Conclusion
motivation
Motivation
  • Saving money for huge content providers such as MS, Youtube
  • Video quality is just acceptable

User BW

++++++

User BW

+

User BW

+++

User demand

+++

Traffic

++

Traffic

+

Traffic

+++

Traffic

++++++++

ISP Charge

+

ISP Charge

+++++++

ISP Charge

++

ISP Charge

+++

P2P

Client Server

Video quality

+++

Video quality

+++

Video quality

+

Video quality

+++++++

p2p architecture
P2P Architecture
  • Peers will assist each other and won’t consume the server BW
  • Each peer have contribution to the whole system
  • Throw the ball back to the ISPs
    • The traffic does not disappear, it moved to somewhere else
outlines1
Outlines
  • Motivation
  • Trace – User demand & behavior
  • Peer assisted VoD
    • Theory
    • Real-trace-driven simulation
  • Cross ISP traffic issue
  • Conclusion
trace analysis
Trace Analysis
  • Using a trace contains 590M requests and more than 59000 videos from Microsoft MSN Video (MMS)
  • From April to December, 2006
video popularity
Video Popularity
  • The more skewed, the much better
download bandwidth
Download bandwidth
  • Use
    • ISP download/upload pricing table
    • Downlink distribution

to generate upload bw distribution

traffic evolution
Traffic Evolution

1.23

2.27

Quality Growth: 50%

User Growth: 33%

Traffic Growth: 78.5%

outlines2
Outlines
  • Motivation
  • Trace – User demand & behavior
  • Peer assisted VoD
    • Theory
    • Real-trace-driven simulation
  • Cross ISP traffic issue
  • Conclusion
p2p methodologies
P2P Methodologies
  • Users arrive with poison distribution
  • Exhaustive search for available upload BW

Video rate: 60

60

70

Total Demand

60 x 4 = 240

100

40

0

30

10

0

Total Support

100+40+30+100 = 270

40

0

100

system status
System status
  • IfSupport >Demand
    • Surplus mode, small server load
  • IfSupport<Demand
    • Deficit mode, VERY large server load
  • IfSupport≈Demand
    • Balanced mode, medium server load
prefetch policy
Prefetch Policy
  • When the system status vibrates between surplus and deficit mode
  • Let every peer get more video data than demand (if possible) in surplus mode
    • And thus they can tide over deficit phase
outlines3
Outlines
  • Motivation
  • Trace – User demand & behavior
  • Peer assisted VoD
    • Theory
    • Real-trace-driven simulation
  • Cross ISP traffic issue
  • Conclusion
methodology
Methodology
  • Event-based simulator
  • Driven by 9 months of MSN Video trace
  • Use greedy prefetch for P2P-VoD
    • For each user i, donate it’s upload BW and aggregated BW to user i+1
    • If user i’s buffer point is smaller than user i+1’s
      • BW allocate to user i+1 is no more than user i
trace driven simulation level
Trace-driven simulationLevel
  • Non-early-departure Trace
  • Non-user-interaction Trace
  • Full Trace
simulation early departure no interaction
Simulation: Early departure (No interaction)
  • When video length > 30mins, 80%+ users don’t finish the whole video
simulation full
Simulation: Full
  • How to deal with buffer holes
    • As user may skip part of the video
  • Two strategies
    • Conservative: Assume that user BW=0 after the first interaction
    • Optimistic: Ignore all interactions
outlines4
Outlines
  • Motivation
  • Trace – User demand & behavior
  • Peer assisted VoD
    • Theory
    • Real-trace-driven simulation
  • Cross ISP traffic issue
  • Conclusion
isp unfriendly p2p vod
ISP-unfriendly P2P VoD
  • ISPs, based on business relations, will form economic entities
    • Traffic do not pass through the boundary won’t be charged
  • ISP-unfriendly P2P will cause large amount of traffic
simulation results of friendly p2p
Simulation results of friendly P2P
  • Peers lies in different economic entities do not assist each other
conclusion pros
Conclusion (Pros)
  • This paper gives a representative trace analysis that breaks the myth of upload BW problems
  • Successfully address the importance of the P2P cross-ISP problem
conclusions cons
Conclusions (Cons)
  • Weak and unrealistic P2P models
  • Unclear comparisons between each P2P strategies and simulations
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