Flow Control in Multimedia Communication Multimedia Systems and Standards S2 IF Telkom University

To make the best use of available network resources at any time and guarantee a maximum level of perceptual video quality from the end-user’s perspective to regulate and control the output bit rates of video sources in the network to achieve the best trade-off between quality and bandwidth utilization 2

challenge to provide a guaranteed quality of service when the network is swamped with excessive delays and information loss rates Congestion avoidance techniques in video communications must consist of an efficient flow control mechanism that regulates the rates of active video sources Video quality degradation 3

Multimedia streaming over the Internet Video and audio streaming over the Internet becomes popular. As last mile network bandwidth increases (ADSL, Cable modems, Satellite), multimedia traffic will constitute a large portion of Internet traffic. The VoD market will grow accordingly (e.g., AOL + TW). 4 Internet

Congestion and flow Control The adaptive, best-effort, congestion control problem End-to-end congestion control. How can we make the best use of the (time varying) bandwidth that is available to our streams? How can we determine what this bandwidth is? How can we track how it changes over time? 5 Switch Fabric Switch Fabric

TCP Constitutes more than 70%-90% of the Internet traffic. Employs AIMD (additive increase and multiplicative decrease) for fairness Congestion indications (packet losses) trigger multiplicative reduction in its transmission rate. 6

TCP background - AIMD Maintains cwnd (congestion window) at the sender by receiving acknowledgment from the receiver; Transmits a cwnd number of packets per round (or per RTT). 7 Packet loss Rounds (reception of cwnd packets) Congestion Window ssThresh Slow start Congestion avoidance Fast recovery (cwnd is halved) TIMEOUT

TCP and TCP-friendliness Non-responsive flows can lock out TCP flows completely; congestion collapse will result. TCP-friendliness: a TCP friendly flow uses the same bandwidth as a competing TCP flow on the same end- to-end path. 8

Multimedia applications Unfortunately, few multimedia streaming commercial applications today employ TCP-friendly flow control. 9

TCP+multimedia applications? Is TCP a good choice for multimedia applications? Not a good marriage. TCP transmission is too bursty ack compression especially under high RTT. TCP’s rate is highly fluctuating A single packet loss can swing the rate to half the current rate or to almost zero under timeout. 10

TCP+multimedia applications? Is TCP a good choice for multimedia applications? Poor performance under asymmetric networks (ADSL,Satellite) Per-packet feedback causes congestion on the reverse path. Feedback loss in the reverse path can cause rate reduction in the forward path. Scalability limitations in multicast environments. Per-packet feedback can cause feedback implosion. 11

Some techniques feedback control mechanism (preventive) the rate control of a video encoder is regulated by modifying some encoding parameters indicated by some feedback messages sent by network receivers that includes some statistics data e.g. average packet transit time, average loss rate for multicast traffic, average packet delay, etc reactive approaches: error concealment video data recovery schemes 12

Feedback approaches SAD(sender-driven AIMD) Jacobs’97, Cen’98, Rejaie’99, etc. Performs AIMD at the sender Provably stable and fair Contains the same limitations as TCP. Per-packet feedback: its performance limitation under asymmetric networks or multicast environments. 13 CWND Time

Feedback approaches MFC (Model-based flow control) or equation-based flow control. Use a stochastic TCP model Mahdavi&Floyd’97,Floyd’99, Padhey’99,etc. Gives a simple analytical formula for TCP throughput in a function of packet loss rate and RTT. Receiver can estimate TCP throughput using the formula. 14 Compute TCP Throughput using the formula. The sender sets its xmission rate to R SenderReceiver Report rate R.

Feedback approaches MFC – fundamental problems. [Ramesh&Rhee’99] analytically shows that under certain circumstances, MFC does not converge to the fair bandwidth. Due to inherent error in estimating loss rates and in the formula. E.g., Under a high transmission rate, the loss rate can be underestimated, and under a low transmission rate, the loss rate can be overestimated. Assumptions made by the model are not universally true. E.g., loss rates or RTTs are not correlated to the transmission rate of the MFC flows. 15 Loss Rate = Number of packets in a window Probability of loss event within a window

Bit Rate Variability of Video Coders All standard video coding algorithms  produce a variable bit rate per frame for a constant quantization parameter 16

Fixed rate 17

Variable rate 18

block-transform video coder Has a variable bit rate characteristics Reasons: The amount of spatial and temporal redundancies detected and suppressed Variable-length coding i.e. Huffman coding 19

Frame size: example 20

CBR or VBR, which one do you prefer? 21

Fixed Rate Coding CBR transmissions are useful for fixed bandwidth channels such as PSTN To achieve  a buffer between the video encoder and the channel is used to smooth out the bit rate fluctuations 22

Buffering  delay must be avoided or at least minimized in real-time video services could only regulate the output bit rate for short-term variations Long-term bit rate fluctuations  large buffer intolerable details Real-time service? 23

Other measures to reduce the burstiness of the output flow of video coders Techniques: feedback control (buffer-based approach) feed-forward control (picture activity) 24

Feedback & feedforward 25

Adjusting Encoding Parameters for Rate Control encoding parameters in block-transform video coders: frame rate encode only the low-frequency coefficients of a block quantization parameter motion detection threshold 26