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End-to-End QoS of Video Delivery over Wireless Internet

End-to-End QoS of Video Delivery over Wireless Internet. QIAN ZHANG, SENIOR MEMBER, IEEE, WENWU ZHU, SENIOR MEMBER, IEEE, AND YA-QIN ZHANG, FELLOW, IEEE. Wen-Shyang Hwang KUAS EE. PROCEEDINGS OF THE IEEE, VOL. 93, NO. 1, JANUARY 2005. Abstract.

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End-to-End QoS of Video Delivery over Wireless Internet

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  1. End-to-End QoS of Video Delivery over Wireless Internet QIAN ZHANG, SENIOR MEMBER, IEEE, WENWU ZHU, SENIOR MEMBER, IEEE, AND YA-QIN ZHANG, FELLOW, IEEE Wen-Shyang Hwang KUAS EE. PROCEEDINGS OF THE IEEE, VOL. 93, NO. 1, JANUARY 2005

  2. Abstract • Key elements in the end-to-end QoS support including: • scalable video representation • network-aware end system • network QoS provisioning • Two approaches in QoS support: • network-centric solution • how to map QoS criterion at different layers respectively • optimize total quality across these layers • network modeling, QoS mapping, and QoS adaptation. • end-system centric solution • network adaptation • available bandwidth estimation • efficient video transport protocol • media adaptation. • error control • power control • corresponding bit allocation

  3. Outline • Introduction • Network-Centric Cross-Layer End-to-end QoS Support • Network QoS provisioning for wireless Internet • Cross-layer QoS support for video delivery over wireless Internet • End-System Centric QoS Support • Network adaptive congestion control • Adaptive error control • Joint power control and error control • Rate-distortion based bit allocation • Conclusion

  4. I. Introduction • QoS support involves several areas: application, terminal, networking architecture, network management, business model, and end user. • Capacity of wireless channel varies randomly with time, providing deterministic QoS(zero QoS violation probability) will waste resources. • Challenges for end-to-end QoS video delivery over wireless Internet: • QoS support involves a wide range of technological aspects. • video coding, physical and link layers support, efficient packet delivery, congestion control, error control, and power control • Diverse QoS requirements (data rate, delay, and packet loss) • video is sensitive to packet delivery delay but tolerate frame losses and transmission errors. • Different types of networks have different characteristics. • mixtures of heterogeneous wireless access technologies co-existed • packet loss in wireless Internet can be congestion loss or erroneous loss • Heterogeneity among end users. • users have different requirements (latency, video visual quality)

  5. Support QoS Requirements • Support QoS requirement in all components of video delivery system from end to end: • QoS provisioning from networks • QoS in wireless networks is different from Internet (IS and DS) • Scalable video presentation from applications • enhancement layers further refine the video quality. • Network adaptive congestion/error/power control in end systems. • controlling transmission power and adjusting transmission rate

  6. Two approaches providing end-to-end QoS support • Network-centric QoS provisioning • Router, switch, base-station, access-point provide prioritized QoS to satisfy data rate, delay bound, packet loss requirements. • At link layer, QoS is expressed in terms of probability of buffer overflow or probability of delay violation. • At video application layer, QoS is measured by mean squared error (MSE) or peak-signal-to-noise ratio (PSNR). • Key issue is the effective QoS mapping across different layer. • how to model the varying network and coordinate effective adaptation of QoS parameters at video application layer and prioritized transmission system at link layer. • End-system centric • congestion control, error control, and power control, to maximize the application-layer video quality without any QoS support from underlying network.

  7. Network-centric Cross-layer End-to-end QoS Support • The solution includes source video encoding, cross-layer QoS mapping and adaptation, prioritized transmission control, adaptive network modeling, and video decoder/output modules.

  8. Network-centric Cross-layer End-to-end QoS Support • In time-varying wireless Internet, dynamic QoS management system interacts with underlying prioritized transmission system to handle: • service degradation • resource constraint. • To offer a good compromise between video quality and available transmission resource • The key is how to provide • an effective cross-layer QoS mapping • an efficient adaptation mechanism.

  9. A. Network QoS Provisioning for Wireless Internet • IETF introduces: • IntServ provides guaranteed and controlled services. • RSVP lack scalability and difficulty in all elements be RSVP. • DiffServ provides a scalable and manageable network with service differentiation capability. • QoS provision in wireless networks: • 3GPP standardizes a common QoS framework for data services, • defined a framework for end-to-end QoS from radio access network through core network to gateway node within UMTS. • defined four UMTS QoS classes according to delay sensitivity: conversational, streaming, interactive, and background classes. • In wireless local area networks • IEEE 802.11e, EDCF establishes a probabilistic priority mechanism to allocate bandwidth based on traffic categories. • WME (Wireless Multimedia Enhancements) provide an interim QoS solution.

  10. B. Cross-Layer QoS Support for Wireless Internet • An efficient QoS mapping scheme that addresses cross-layer QoS issues for video delivery over wireless Internet includes: • wireless network modeling • effectively model time-varying and nonstationary behavior of wireless networks • prioritized transmission control scheme • derive and adjust the rate constraint of a prioritized transmission system • QoS mapping and adaptation mechanism • optimally map video application classes to statistical QoS guarantees of a prioritized transmission system • provide best tradeoff between video application quality and transmission capability under time-varying wireless networks.

  11. Wireless Network Modeling • model a communication channel at different layers • physical layer • classified into radio-layer channel, modem-layer channel, and codec-layer channel. • link-layer

  12. Physical layer models • radio-layer channel models can be classified into • large-scale path loss models • characterize the underlying physical mechanisms (reflection, diffraction, scattering) for specific paths. • small-scale fading models • describe the characteristics of generic radio paths in a statistical fashion. • Modem-layer channel can be modeled by a finite-state Markov chain • states are characterized by different BERs. • codec-layer channel can be modeled by a finite-state Markov chain • states are characterized by different data-rates, or a symbol being error-free/in-error, or a channel being good/bad • existing physical-layer channel models are complex to characterize the relationship between control parameters and calculated QoS measures.

  13. Prioritized Transmission Control • For differentiated services, a class-based buffering and scheduling mechanism is needed. • each QoS priority class can obtain a certain level of statistical QoS guarantees in terms of probability of packet loss and packet delay. • translate the statistical QoS guarantees of multiple priority classes into rate constraints based on the effective capacity theory. • rate constraints specify the maximum data rate that transmitted reliably with statistical QoS guarantee over time-varying wireless channel. • video substreams can be classified into classes, and bandwidth can be allocated accordingly for each class. • The rate constraint of multiple priority classes under a time-varying service rate channel can be derived according to the guaranteed packet loss probabilities and different buffer sizes of each priority class.

  14. QoS Mapping and QoS Adaptation • Mapping and adaptation: to match QoS criterion across different layers. • QoS measurement are not directly related at below two layers • video application layer: distortion and uninterrupted video service perceived by end-users • link layer: packet loss/delay probability • At video application layer, each video packet is characterized based on its loss and delay properties. • Video packets are classified and optimally mapped to the classes of link transmission module under the rate constraint. • QoS mapping and adaptation for wireless network was addressed: • find optimal mapping policy from one GOP (group of picture) to K priority classes. • find a set of QoS parameters for priority network

  15. III. End-System Centric QoS Support • video applications should be aware of and adaptive to the variation of network condition in wireless Internet. • The adaptation consists of network adaptationand media adaptation.

  16. Adaptation • Network adaptation: • how many network resources (bandwidth and battery power) for the video • design an adaptive media transport protocol for video delivery. • Adaptive Network Monitor: • probing and estimating the dynamic network conditions. • Congestion Controlmodule: • adjusts sending rate based on the feedback information. • Media adaptation • controls bit rate of video based on estimated available bandwidth • adjusts error and power control according to wireless Internet conditions. • Network-aware Unequal Error Protection (UEP) module • protects different layers against congestive packet losses and erroneous losses according to their importance and network status. • Network-aware Transmission Power Adjustmentmodule • adjusts transmission power to affect wireless channel conditions. • R-D Based Bit Allocationmodule • performs media adaptation control with two different targets, i.e., distortion-minimization and power consumption-minimization.

  17. A. Network Adaptive Congestion Control • Congestion-control mechanism takes the form of rate control at end systems to reduce packet loss and delay. • Involved protocols: RTP, RTCP, SDP, RTSP, SCTP, SIP, and HTTP. • Two types of TCP-friendly flow-control protocols for multimedia: • Sender-based rate adjustment: performs AIMD rate control as TCP. • Model-based flow control: a stochastic TCP model to represent TCP throughput as a function of packet loss ratio and RTT. • The issues of network condition estimation for designing transport protocol for video transmission over wireless Internet • estimation of congestion loss ratio. (end-to-end packet loss can be caused by either congestion loss or erroneous loss) • round trip time (RTT) estimation • available bandwidth estimation.

  18. End-to-End Packet Loss Differentiation and Estimation • Two types of methods to distinguish the network status: • split connection method: agent at the edge of wired and wireless network to measure network conditions separately. • end-to-end method: adopt heuristic methods such as interarrival time or packet pair. • Two types of approaches for available bandwidth estimation: • based on the estimated RTT and packet loss ratio. • using the Receiver Based Packet Pair (RBPP) method. • requires the use of two consecutively sent packets to determine a bandwidth share sample.

  19. Adaptive Error Control • Two basic error correction mechanisms: ARQ and FEC. • ARQ is more effective than FEC. FEC has strict delay requirements. • Hybrid ARQ scheme achieve both delay bound and rate effectiveness by limiting the number of retransmissions. • Some discussions on hybrid FEC and delay-constrained ARQ schemes: • protection strategies applied to video over cellular networks • integrated packetization, scheduling, and protection strategies for wireless transmission of nonscalable coded video. • video-optimized error resilience techniques for compressed video. • resilient real-time video streaming over IEEE 802.11b WLANs for both unicast and multicast transmission. • Scalable video has fast adaptation characteristic. • unequal error protection (UEP): strong channel-coding protection for base layer, weaker channel-coding for enhancement layer. • how to add FEC to scalable video coding has great interest recently.

  20. Joint Power Control and Error Control • tradeoff between quality of video application and power consumption • processing power and transmission power at end-systems • The point of view: • From network: multipath fading and multiple access interference (MAI) use high transmission power. • From video coding: to decrease transmission power, more complex compression algorithms and channel coding schemes are applied. • From individual user: allocate available bits for source and channel coders to minimize total processing power consumption. • From group user: • changetransmission power of one user will alter other users’ receiving (signal-tointerference ratio) SIRs and video quality. • due to multiple access interference, the global minimization of power consumption must be investigated

  21. Rate, Distortion and Power Consumption • Observe relationship among rate, distortion, and power consumption. • According to rate-distortion theory, the lower source coding rate R, the larger distortion • power-constrained distortion includes both distortion by the source rate control R and distortion caused by power constraint P • end-to-end distortion is composed of the distortion by source rate control R, the distortion caused by the channel errors E, and the distortion caused by the power constraint P

  22. Rate-Distortion Based Bit Allocation • metrics to evaluate video quality • expected end-to-end distortion • source distortion: caused by source coding such as quantization and rate control. • channel distortion:packet loss due to network congestion or wireless link error. • expected end-to-end power consumption. • includes processing power on source coding, processing power on channel coding, and transmission power for data delivery. • important to efficiently allocate bits among source coding and channel coding under fixed bandwidth capacity • minimal expected end-to-end distortion • minimal expected end-to-end power consumption

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