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Multi-layer Active Queue Management and Congestion Control for Scalable Video Streaming

Kang, S.-R.; Zhang, Y.; Dai, M.; Loguinov, D.;Distributed Computing Systems, 2004. Proceedings. 24th International Conference on , 24-26 March 2004

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Core components

Priority Active Queue Management mark packets of different importance and drop

less important packets first Congestion Control

feedback network information from router and adjust the frame size

Partitioned Enhancement Layer Streaming (PELS) priority marking, AQM, congestion control

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Outline

Background Best-effort network is not enough AQM Congestion control Simulation Conclusion

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Goal

majority of packets across bottleneck carry useful information

retransmission-free

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MPEG-4 FGS

base layer is more important than enhancement layer

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Best-Effort Streaming

assume independent Bernoulli packet loss with probability p, expected number of useful packets (consecutively received) is

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Best-Effort Streaming

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Optimal Preferential Streaming goal: achieve U = 1 in order to be optimal, upper layer should be

dropped before lower layer enhancement layers further divide into two

layers

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Active Queue Management

two types of queues: PELS queue and Internet queue

Weighted round-robin (WRR)

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Active Queue Management

send low-priority packets only after all high-priority packets are sent

no end-user can gain by marking all packets with highest priority

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Selection of γ pR = pxi/γxi = p/γ = pthr

optimistic: pthr~1 U~1 pessimistic: pthr~p γ =1

yellow layer = (1- γ)xi = 0 close-form expression for γ

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Selection of γ

when p=0.1, pthr=0.75, U>=0.96 when p=0.01, pthr=0.75, U>=0.996

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Congestion control

modified from Kelly’s control (a game-theoretic and optimization method), discrete version called Max-min Kelly Control (MKC)

reduce bitrate and keep waste to minimum

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Simulation

ns2 simple bar-bell topology 1 video frame

= 63000 bytes = 126 packets(21 base layer packets)

50% bottleneck forTCP cross traffic

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Stability properties ofγ show that

γis stable in the close-form expression with dynamic loss prob;

by using found γ , loss prob of red packets kept to target threshold

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Delay characteristic of PELS

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Fairness of MKC congestion control

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Conclusion

preferential streaming framework (PELS) provides high level of end-user QoS

independent of underneath congestion control methods