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Experience with Control Mechanisms for Packet Video in the Internet. J-C. Bolot and T. Turletti. Presented by Michael Wong Course 18-845, 4/25/00. Outline. Introduction Rate control mechanisms Loss control mechanisms Limitations and outlook Conclusion. Conventional Video.

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Experience with Control Mechanisms for Packet Video in the Internet

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Experience with control mechanisms for packet video in the internet

Experience with Control Mechanisms for Packet Video in the Internet

J-C. Bolot and T. Turletti

Presented by Michael Wong

Course 18-845, 4/25/00


Outline

Outline

  • Introduction

  • Rate control mechanisms

  • Loss control mechanisms

  • Limitations and outlook

  • Conclusion


Conventional video

Conventional Video

  • Rate of video sequence vary rapidly with time

  • Constant capacity channel

  • Solution: Vary video quality according to scene complexity so as to keep output rate approx. constant

  • Rate control based on buffer feedback


Best effort service

Best effort service

  • Offer channel with characteristics:

    • Available bandwidth, end-to-end delay and loss

  • Dependent on other connections in the network

  • Difficult to determine a priori


Approach 1

Approach 1

  • Provide performance guarantees at network level

  • Requires specific resource allocation and/or reservation mechanisms

  • Not widely deployed


Approach 2

Approach 2

  • Adapt application behavior to network characteristics

  • Also applicable to network with explicit resource allocation and reservation


Focus

Focus

  • End-to-end delay requires elaborate queuing disciplines

  • Delay control with adaptive playout algorithms is a well understood problem

  • Adapt to available bandwidth and loss

    • Rate control mechanisms

    • Error control mechanisms


Rate control mechanisms

Rate control mechanisms

  • Examples of source-based control:

    • TCP – Adjust window size based on network congestion

    • CATV – Local buffer capacity

    • WAN – Feedback information on state of network


Difficulties

Difficulties

  • Characteristics of channel is time varying

  • Variations dependent on other traffic sources

  • The “channel” is a heterogeneous multicast tree


Rate adjustment

Rate adjustment

  • Parameters for block-based transform video encoding

    • Frame sampling rate (PQ mode)

    • Quantization levels (PR mode)

    • Movement detection threshold (PR mode)

  • User specifies mode and max_rate


Feedback collection

Packets sent using Real-Time Transport Protocol (RTP)

Feedback carried by RTCP packets as Receiver Reports (RR)

0 1 2 3

0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1

+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+

|V=2|P|X| CC |M| PT | sequence number |

+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+

| timestamp |

+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+

| synchronization source (SSRC) identifier |

+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+

| contributing source (CSRC) identifiers |

| .... |

+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+

Feedback collection


Rate control algorithm

Rate control algorithm

  • Maximum output rate is controlled by linear increase/multiplicative decrease algorithm:

    If Congestion

    max_rate := max(max_rate/GAIN, MIN_RATE)

    Else if NoCongestion

    max_rate := min(max_rate + INC, MAX_RATE)


Observations

Observations

  • Algorithm can be used in PQ or PR mode

  • Rate control vs. window control in TCP

  • Rate adjustments do not match window adjustments in TCP

  • No good values of Congestion, NoCongestion, GAIN, and INC.


Rate control cont d

Rate control (cont’d)

  • Analytic models of TCP, bandwidth equ of a TCP connection [23],

    • MTU = maximum packet size

    • rtt = mean round trip time

    • p = mean packet loss rate


Limitations

Limitations

  • Feedback explosion

    • Probabilistic sampling scheme in IVS

    • Scaled feedback scheme of RTCP

  • Heterogeneity problem

    • Convert loss rates into a global loss rate

    • Average or highest loss rate


Experimental evaluation

Experimental evaluation

Unicast over INRIA

Slow CPU


Experimental evaluation cont d

Experimental Evaluation (cont’d)

One Source

Three Sources


Experimental evaluation cont d1

Experimental Evaluation (cont’d)


Loss control mechanisms

Loss control mechanisms

  • Lost packets degrade video quality

  • Intracoded frames sent at regular intervals

  • Approaches to loss control:

    • Reduce the time between intra-coded blocks of image

    • Intra-code and transmit only blocks that change the most

    • Use intra- and inter-frame coding (IVS)


Loss control cont d

Loss control (cont’d)

  • Destination recovery

    • Recover at destination using loss concealment techniques (i.e. spatial and temporal interpolation)

    • Forward Error Correction (FEC)-based error control mechanisms


Loss control using fec

Loss control using FEC

  • Redundant data about packet n – k in packet n is made up of macroblocks (MB)

  • MBs are stored at lower definition

  • Feedback mechanism is used to control the amount of redundant information sent by source


Fec loss rate

FEC loss rate


Experimental evaluation1

Experimental Evaluation


Limitations and outlook

Limitations and Outlook

  • Source-based control mechanisms

    • Heterogeneity of network exhibit widely different characteristics

    • Either low capacity participants are overwhelmed or

    • High capacity participants receive low quality video


Solutions

Solutions

  • Video gateways

  • Layered coding

    • Encode video with a layered or hierarchical coding scheme

    • Receivers join one or more multicast groups suited to network conditions

    • “Shared learning” to prevent load explosion


Solutions cont d

Solutions (cont’d)

  • Replace join experiments by an explicit estimation at each receiver of equ

  • Find the largest integer L s.t.

  • Advantages

    • TCP-friendly

    • Does not rely on active probing

    • Does not require shared learning


Conclusion

Conclusion

  • Prevents real-time UDP apps from swamping Internet and TCP

  • Rate adjustment algorithm and rate parameters unclear

  • Scalability issues with heterogeneous multicast groups

  • No minimum quality guarantees


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