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Layer-Encoded Video in Scalable Adaptive Streaming

Michael Zink, Jens Schmitt,and Ralf Steinmetz, Fellow, IEEE

IEEE TRANSACTIONS ON MULTIMEDIA, VOL. 7, FEBRUARY 2005

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Outline

What is scalable adaptive streaming?Maximize the quality of the cached video

Average PSNR is not a good assessmentSubjective impression of variations in layer-encoded video

Retransmission schedulingSimulation resultsConclusion

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What is scalable adaptive streaming

Main goal:Provide a true video-on-demand (TVoD) system

Issues:Quality Adaptation (congestion control)

Layer-encoded techniqueScalability (performance)

Proxy caching

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How to assess the quality of video

Use a subjective assessment

The experiment was performed with 94 test candidates

(62 males and 32 females), between the age of 14 and 64.

Video:Consists of 4 layersThe size of the nth layer:

sn = 2sn-1

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Subjective assessment v.s PSNR (1/2)

Six variations in layer-encoded video

Farm1–Amplitude: Decrease slightly has better quality

Farm2–Frequency: Lesser layer changes has higher quality

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Subjective assessment v.s PSNR (1/2)

M&C1–Closing the Gap:Close a gap in a lower layer has higher quality

M&C2–Constancy:No layer changes has better quality

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Subjective assessment v.s PSNR (2/2)

M&C3–Constancy at a Higher Level:

Tennis1–All is Well That Ends Well:Increasing the amount of layers in the end leads to a higher quality

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Compare Subject and PSNR quality

Subject assessment is more precise than PSNR. s(v) represents the same result as subject assessment.

Minimize the frequency and amplitude will have the better quality (reducing the layer variations).

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When to schedule the retransmissions

Retransmission time:Directly after the initial streaming processDuring subsequent requestsDuring requests for different content from the server

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How to schedule the retransmissions

Scheduling goals:Decreasing quality variations for a cached video is important.Minimize both frequency of variations and amplitude of variations.

s(v): spectrum

frames

layer

s

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Algorithms for retransmission scheduling (1/3)

Optimal retransmission schedulingis a discrete nonlinear stochastic optimization problem (NP-complete)

Heuristics for retransmission schedulingUnrestricted priority-based heuristics

Send periodic retransmission requests to the server to ensure that the server obtains an up-to-date schedule of retransmissions.

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Algorithms for retransmission scheduling (2/3)

Three heuristics of unrestricted priority-based retransmission scheduling algorithm:

Case1 : Unrestricted lowest layer first (U-LLF)

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Algorithms for retransmission scheduling (3/3)

Case2 : Unrestricted shortest gap lowest layer first (U-SG-LLF)

Case3 : Unrestricted lowest layer shortest gap first (U-LL-SGF)

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Simulation results (1/2)

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Simulation results (2/2)

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Conclusion

Promise a scalable TCP-friendly TVoD system

Scalable adaptive systemUse both caching and layer-encoded

Develop the retransmission algorithms to retransmit missing segments

Minimize the frequency and amplitude of the variations of the cached video