Adaptive QoS Control of Multimedia Transmission Over Band-limited Networks Presenter: Hu Huang Nov. 2002 G.Y.Hong 1, Member, IEEE, A.C.M.Fong 1, Member,

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Presentation transcript:

Adaptive QoS Control of Multimedia Transmission Over Band-limited Networks Presenter: Hu Huang Nov G.Y.Hong 1, Member, IEEE, A.C.M.Fong 1, Member, IEEE, B.Fong 2, Member, IEEE 1 IIMS, Massey University, 2 Auckland University of Technology IEEE Transactions on Consumer Electronics, Vol.48, No.3, AUGUST 2002

Background Users of next generation communication devices (cellular phones and PDAs) will increasingly require access to multimedia contents(video etc.) on internet, which places heavy demand on the Quality of service(QoS) control mechanism due to limited network bandwidth resources, varying channel conditions(e.g. fading) and limited device capabilities(e.g. processing power, display size). The heterogeneous nature of the Internet and other band-limited networks means that it is often unrealistic to rely on network routers for QoS support. In contrast, application-layer QoS mechanisms that do not rely on the network tend to provide most robust solutions and are compatible with even very poor network condition, which may also be time varying. So, an adaptive and robust QoS algorithm (from transport perspective) for band-limited networks was proposed in this paper.

Contents Current application-layer QoS control techniques Proposed adaptive QoS control approach Experimental results Conclusion

Current Application-Layer QoS Control Techniques ( for multimedia data transmission over band-limited networks ) Application-layer QoS control Congestion ControlError Control Rate Control (sender and /or receiver) Rate ShapingRetransmissionChannel-based FEC Fig. 1 Application-layer QoS control (transport perspective)

Adaptive QoS Control ( approach described in this paper )

Adaptive QoS Control (Cont.) An adaptive QoS control mechanism that adapts to network conditions as perceived by each receiver has been proposed.

Adaptive QoS Control (Cont.) Rate Control Receiver side : Model-based control (Bernoulli model) packet loss detection: threshold =3 packet loss ratio r = n L /n (within one sampled period) smoothed loss ratio j =  j-1 +(1-  )r j (  =0.33) Transmitter Side: AIMD (Additive Increase and Multiplicative Decrease) rate adjustment: Appropriately loaded  transmission rate to that receiver is not changed Heavily loaded  transmission rate is aggressively decreased Lightly loaded  transmission rate is gradually increased depending on j

Adaptive QoS Control (Cont.) Rate shaping with multiple quantization parameters Purpose: produce scalable multimedia data streams for different transmission rates for different receivers at different times, achieving optimal match between network resources, devices capabilities and transmission rate. Transformed Data -- Q 1 (QP 1 )->EC Q 2 (QP 2 )->EC Q N (QP N )->EC Bitstream 1 Bitstream 2 Bitstream N In the proposed approach, N =3 to obtain three bitstreams of different quality (Bitstream 3 is the highest quality while Bitstream 1 is the least). Fig. 4 Rate shaping with multiple QP

Adaptive QoS Control (Cont.) Adaptive Forward Error Correction (FEC) d1d1 d2d2 d3d3 dkdk P ………………… P=d 1 d 2 d 3 … d k   K= ( , 16, 8, 4, 2) depending on the prevailing network condition. (e.g. K=  indicates P is not employed at all due to good network condition). j is used to determine the appropriate degree of protection. Fig.5 Transmitted data stream Each block of K primary data packets has a parity packet P appended to it, which is used for recovering lost packets.

Experimental Results PSNR=20 lg[(2 b -1)/RMSE] (PSNR: peak signal-to-noise ratio; RMSE: root mean squared error) The results indicate that the new scheme consistently outperformed the standard MPEG codec with fewer fluctuations. Average improvement of 0.5dB PSNR can be achieved over standard MPEG implementation.

Conclusion The proposed mechanism combines explicit estimation network condition for additive increase multiplicative decrease (AIMD) rate control, rate shaping with multiple quantization parameters(QP), and adaptive FEC into an integrated scheme. Not only sender but also receivers actively participate in the close-loop feedback control scheme, which makes the mechanism adaptive to varying network conditions as experienced by each receiver.

End Thanks!