realtime multimedia streaming over internet
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Realtime Multimedia Streaming over Internet. Pengjun Pei Dazhen Pan CSE 620 Fall,2001. Overview. Wide Application Video-conference Internet telephony Streaming audio/video players Challenges:Internet is best-effort network Packet loss Bandwidth variation Packet delay variation. - PowerPoint PPT PresentationTRANSCRIPT
Realtime Multimedia Streaming over Internet
Pengjun PeiDazhen Pan
CSE 620 Fall,2001
Overview
Wide Application Video-conference Internet telephony Streaming audio/video players
Challenges:Internet is best-effort network Packet loss Bandwidth variation Packet delay variation
System Architecture
Content
Video CompressionCongestion ControlError Control
Video Compression
Various requirement: Bandwidth Delay Loss VCR like function Decoding complexity
Intra-frame redundancy & inter-frame redundancyNon-scalable coding vs Scalable coding
Inter-frame redundancy
MPEG-2:
I frame: intra-picture P frame: predicted pictureB frame: bi-directional predicted pictureMPEG frame dependencies in an MPEG bit
stream
Scalable Coding
FGS: fine granularity scalability(proposed to MPEG-4):
Bitplanes of enhancement DCT coeffients
Content
Video CompressionCongestion ControlError Control
Congestion Control
Requirements for multimedia streaming Relatively constant rate Low latency for packet delivery Small latency variance Timely delivery is more important than
complete reliability
Rate controlRate shaping
TCP/UDP?
TCP Retransmission mechanism
intolerable delays Multiplicative decrease in case of
congestionsharp variation in visual effect
UDP Unfair to responsive TCP flows Congestion collapse
Categories of Rate Control
Source-based rate controlSource adjusts sending rateFeedback employedCan be applied to both unicast and
multicast
Receiver-based rate controlReceiver joins layer/channel Used in multicasting scalable video
Hybrid rate control
TCP Friendly Flows
A flow is TCP-friendly if its arrival rate does not exceed the bandwidth of a conformant TCP connection in the same circumstances.
TCP throughput model
λ: throughput of a TCP connection
MTU: maximum transit unitRTT: Round Trip Timep: packet loss ratio
pRTT
MTU
*
*325.1
RAP(Rate Adaptation Protocol)
Proposed by R. Rejaie 1998End-to-end architecture
RAP
Decision function If no congestion is detected, periodically increase the
transmission rate If congestion is detected, immediately decrease the
transmission rate
Increase/Decrease algorithm: AIMDDecision frequency
Smoothed version of one RTT: most recent value of SRTT
RAPDecision function
Mechanisms to detect loss: Timeout
SRTTi = 7/8 * SRTTi + 1/8 * SampleRTTTimeout=μ*SRTT+δ*VarRTTUse transmission history ’coz it isn’t ack-clockedBefore sending a new packet, source traverses through the transmission history and detects all timeout losses: WHILE (DepartTimei+Timeout>=CurrTime)
IF(Flagi!=Acked) THENSeqi is lost
Detect a burst of loss at once
RAP Decision function(Continued)
Gaps in sequence number(ACK-based)
ACK Packet:Acurr:packet being acknowledged
N: the last packet before Acurr that was still missing
Alast:the last packet before N that was received Timeout mechanism as a backup for critical
scenarios such as when a burst of packets is lost
AIMD in RAP
No-packet loss: Si = Si + α (step height) Si = PacketSize/IPGi IPGi+1 = IPGi*C/( IPGi + C ) α = Si+1 – Si = PacketSize/C
Upon packet loss: Si+1 = β*Si IPGi+1 = IPGi/β β = 0.5
IPG:inter-packet-gap
RAP Decision Frequency
Adjust IPG once every round-trip time using most recent value of SRTTRight value of C: C must be adjusted so that in a steady state,
the number of packets transmitted per step is increased by 1.
If IPG is updated once every T seconds and we choose C = T/k, the # of packets sent during each step is increased by k every step.
RAP use k=1 to emulate the TCP window adjust
RAP Fine-grain rate adaptation
Motivation:Make RAP more stable and responsive to transient
congestion while still performing the AIMD algorithm at a coarser granularity
Fine-grain feedback:Feedbacki=FRTTi/XRTTiFRTTi,XRTTi: short/long term exponential moving
average of RTT samples at the ith adjusting pointRTTi+1 = (1 – K)RTTi+K*SampleRTT(KXRTT=0.01 KFRTT=0.9)
Fine-grain adjustmentIPGi’ = IPGi * Feedbacki
Simulation Result RAP
Simulation Result(FG-RAP)
Binomial Algo
Proposed by D. Bansal 2000
I: Increase in window as a result of receipt of one window of ACK in a RTTD:Decrease in window on detection of a loss by the senderWt: window size at time t
10:
0;/:
ltttt
kttRt
D
I
Properties of Binomial Algo
Any l < 1 has a decrease that is in general less than a multiplicative decreaseTCP Friendly if and only ifk + l = 1 and l <= 1 for suitable α and β.Converge to fairness as long ask > =0, l >= 0, k + l > 0
10:
0;/:
ltttt
kttRt
D
I
Ratio of throughput AIMD/Binomial
x:value of ky:TCP throughput/Binomial throuput
SQRT(k = l = 0.5)
SQRT vs AIMD
SQRT has less oscillatory bandwidth probing
Categories of Rate Control
Source-based rate controlSource adjusts sending rateFeedback employedCan be applied to both unicast and
multicast
Receiver-based rate controlReceiver joins layer/channel Used in multicasting scalable video
Hybrid rate control
Source-based Rate Control for Multicast
Unicast video distribution using multiple point-point connectionMulticast video distribution using point-to-multipoint transmission
Single-Channel Multicast
IVS(INRIA Video-conference System): Single-channel multicast Probe-base,use AIMD Each receiver determine the network
status Source solicits network status info
through probabilistic polling to avoid feedback implosion
Compare the fraction of congested receiver with threshold
Multiple-channel multicast
Differentiated service to receivers because each receiver can individually negotiate service parameters with the recourseBandwidth inefficiency
Categories of Rate Control
Source-based rate controlSource adjusts sending rateFeedback employedCan be applied to both unicast and
multicast
Receiver-based rate controlReceiver joins layer/channel Used in multicasting scalable video
Hybrid rate control
Receiver-based Rate Control
Typically applied to layered multicast video Source-based works reasonably well for
unicast Receiver-based targeted at solving
heterogeneity problem in the multicast case
Probe-based: No congestion, receiver probes for available
bandwidth by joining layer/channel When congested,receiver drops a layer
Receiver-based Rate Control
Model-based: Based on throughput model of TCP γi:transmission rate of Layer I, L current highest
layer Starts with subscribing base layer(Layer 0), set
L=0. Obtain MTU,RTT, p for a given period, calculate
throughput λ . If λ < γ0 drop base layer and stop receiving
video Else determine L’ ,the largest integer such that
'
0
L
i i
Categories of Rate Control
Source-based rate controlSource adjusts sending rateFeedback employedCan be applied to both unicast and
multicast
Receiver-based rate controlReceiver joins layer/channel Used in multicasting scalable video
Hybrid rate control
Hybrid Rate Control
Targeted at multicast videoApplicable to both layered video and non-layered videoMultiple channels, sender dynamically adjusts the rate for each channelDSG(Destination Set Grouping) Multiple streams:same video info with different
rate and quality,each sent to an IP multicast group Receiver chooses a multicast group to join Source uses feedback to adjust rate for each
stream
Rate Shaping
Adapt the rate of compressed video bit-streams to the target rate constraint
Types of rate filter
Codec Filter: perform transcoding between different schemesFrame-dropping filter:distinguish frame types and drop frames according to importanceLayer-dropping filter:distinguish layers and drop frames according to importanceFrequency filter:discard DCT coefficient of high frequencies
Conclusion
Binomial rate control causes less oscillation to multimedia stream
Current research separates rate control and rate shaping
Main ReferenceDeepak Bansal and Hari Balakrishnan ,Binomial Congestion ControlProc. IEEE INFOCOM Conf., Anchorage, AK, April 2001. S.Floyd, M. Handley,J.Padhye, and J. Widmer, Equation-Based Congestion Control for Unicast Applications, Proc. ACM SIGCOMM’00, pages43-54, Stockholm,Sweden,September 2000International Organization for Standardization. Overview of the MPEG-4 Standard,December 1999Sally Floyd,Kevin Fall, Promoting the Use of End-to-End Congestion Control in the Internet IEEE/ACM Transaction on Networking,May 1999Dapeng Wu,Yiwei Thomas Hou,etc, Streaming Video over the Internet: Approaches and Directions IEEE Transaction on Circuits and System for Video Technology, Vol11,No1,February 2001Dapeng Wu, Yiwei Thomas Hou,etc, Transorting real-time video over the Internet:challenges and approaches, Proceedings of the IEEE, vl.88,no. 12, Dec.2000R.Padhye,J.Kurose,D.Towsley,and R.Koodi. A Model-based TCP-Friendly Rate Control Protocol. In Proc. IEEE NOSSDAV’99,Basking Ridge,New Jersey,June 1999R.Rejaie,M.Handely,and D.Estrin. RAP:An End-to-end Rate-based Congestion Control Mechanism for Realtime Streams in the Internet. In Proc. IEEE Infocom’99,New York,NY,March 1999