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Versions: 00 01 02 03 draft-alvestrand-rmcat-congestion

Network Working Group                                          H. Lundin
Internet-Draft                                                 S. Holmer
Intended status: Informational                        H. Alvestrand, Ed.
Expires: March 8, 2012                                            Google
                                                       September 5, 2011


  A Google Congestion Control for Real-Time Communication on the World
                                Wide Web
                 draft-alvestrand-rtcweb-congestion-00

Abstract

   This document describes two methods of congestion control when using
   real-time communications on the World Wide Web (RTCWEB); one sender-
   based and one receiver-based.

   It is published to aid the discussion on mandatory-to-implement flow
   control for RTCWEB applications; initial discussion is expected in
   the RTCWEB WG's mailing list.

Requirements Language

   The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT",
   "SHOULD", "SHOULD NOT", "RECOMMENDED", "MAY", and "OPTIONAL" in this
   document are to be interpreted as described in RFC 2119 [RFC2119].

Status of this Memo

   This Internet-Draft is submitted in full conformance with the
   provisions of BCP 78 and BCP 79.

   Internet-Drafts are working documents of the Internet Engineering
   Task Force (IETF).  Note that other groups may also distribute
   working documents as Internet-Drafts.  The list of current Internet-
   Drafts is at http://datatracker.ietf.org/drafts/current/.

   Internet-Drafts are draft documents valid for a maximum of six months
   and may be updated, replaced, or obsoleted by other documents at any
   time.  It is inappropriate to use Internet-Drafts as reference
   material or to cite them other than as "work in progress."

   This Internet-Draft will expire on March 8, 2012.

Copyright Notice

   Copyright (c) 2011 IETF Trust and the persons identified as the
   document authors.  All rights reserved.



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   This document is subject to BCP 78 and the IETF Trust's Legal
   Provisions Relating to IETF Documents
   (http://trustee.ietf.org/license-info) in effect on the date of
   publication of this document.  Please review these documents
   carefully, as they describe your rights and restrictions with respect
   to this document.  Code Components extracted from this document must
   include Simplified BSD License text as described in Section 4.e of
   the Trust Legal Provisions and are provided without warranty as
   described in the Simplified BSD License.


Table of Contents

   1.  Introduction . . . . . . . . . . . . . . . . . . . . . . . . .  3
     1.1.  Mathemathical notation conventions . . . . . . . . . . . .  3
   2.  System model . . . . . . . . . . . . . . . . . . . . . . . . .  4
   3.  Receiver side control  . . . . . . . . . . . . . . . . . . . .  4
     3.1.  Arrival-time filter  . . . . . . . . . . . . . . . . . . .  5
     3.2.  Over-use detector  . . . . . . . . . . . . . . . . . . . .  8
     3.3.  Rate control . . . . . . . . . . . . . . . . . . . . . . .  8
   4.  Sender side control  . . . . . . . . . . . . . . . . . . . . . 10
   5.  Interoperability Considerations  . . . . . . . . . . . . . . . 11
   6.  Implementation Experience  . . . . . . . . . . . . . . . . . . 12
   7.  Further Work . . . . . . . . . . . . . . . . . . . . . . . . . 12
   8.  IANA Considerations  . . . . . . . . . . . . . . . . . . . . . 13
   9.  Security Considerations  . . . . . . . . . . . . . . . . . . . 13
   10. Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . 13
   11. References . . . . . . . . . . . . . . . . . . . . . . . . . . 13
     11.1. Normative References . . . . . . . . . . . . . . . . . . . 13
     11.2. Informative References . . . . . . . . . . . . . . . . . . 14
   Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . . 14




















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1.  Introduction

   Congestion control is a requirement for all applications that wish to
   share the Internet [RFC2914].

   The problem of doing congestion control for real-time media is made
   difficult for a number of reasons:

   o  The media is usually encoded in forms that cannot be quickly
      changed to accomodate varying bandwidth, and bandwidth
      requirements can often be changed only in discrete, rather large
      steps

   o  The participants may have certain specific wishes on how to
      respond - which may not be reducing the bandwidth required by the
      flow on which congestion is discovered

   o  The encodings are usually sensitive to packet loss, while the real
      time requirement precludes the repair of packet loss by
      retransmission

   This memo describes two congestion control algorithms that together
   are seen to give reasonable performance and reasonable (not perfect)
   bandwidth sharing with other conferences and with TCP-using
   applications that share the same links.

   The signalling used consists of standard RTP timestamps [RFC3550],
   standard RTCP feedback reports and Temporary Maximum Media Stream Bit
   Rate Requests (TMMBR) as defined in [RFC5104] section 3.5.4.

1.1.  Mathemathical notation conventions

   The mathematics of this document have been transcribed from a more
   formula-friendly format.

   The following notational conventions are used:

   X_bar  The variable X, where X is a vector - conventionally marked by
      a bar on top of the variable name.

   X_hat  An estimate of the true value of variable X - conventionally
      marked by a circumflex accent on top of the variable name.

   X(i)  The "i"th value of X - conventionally marked by a subscript i.







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   [x y z]  A row vector consisting of elements x, y and z.

   X_bar^T  The transpose of vector X_bar.


2.  System model

   The following elements are in the system:

   o  Incoming media stream

   o  Media codec - has a bandwidth control, and encodes the incoming
      media stream into an RTP stream.

   o  RTP sender - sends the RTP stream over the network to the RTP
      receiver.  Generates the RTP timestamp.

   o  RTP receiver - receives the RTP stream, notes the time of arrival.
      Regenerates the media stream for the recipient.

   o  RTCP sender at RTP sender - sends sender reports.

   o  RTCP sender at RTP receiver - sends receiver reports and TMMBR
      messages.

   o  RTCP receiver at RTP sender - receives receiver reports and TMMBR
      messages, reports these to sender side control.

   o  RTCP receiver at RTP receiver.

   o  Sender side control - takes loss rate info, round trip time info,
      and TMMBR messages and computes a sending bitrate.

   o  Receiver side control - takes the packet arrival info at the RTP
      receiver and decides when to send TMMBR messages.

   Together, sender side control and receiver side control implement the
   congestion control algorithm.


3.  Receiver side control

   The receive-side algorithm can be further decomposed into three
   parts: an arrival-time filter, an over-use detector, and a remote
   rate-control.






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3.1.  Arrival-time filter

   This section describes an adaptive filter that continuously updates
   estimates of network parameters based on the timing of the received
   frames.

   At the receiving side we are observing groups of incoming video
   packets, where each group of packets corresponding to the same frame
   having timestamp T(i).

   Each frame is assigned a receive time t(i), which corresponds to the
   time at which the whole frame has been received (ignoring any packet
   losses).  A frame is delayed relative to its predecessor if t(i)-t(i-
   1)>T(i)-T(i-1), i.e., if the arrival time difference is larger than
   the timestamp difference.

   We define the (relative) inter-arrival time, d(i) as

     d(i) = t(i)-t(i-1)-(T(i)-T(i-1))


   Since the time ts to send a frame of size L over a path with a
   capacity of C is

     ts = L/C


   we can model the inter-arrival time as

              L(i)-L(i-1)
     d(i) = -------------- + w(i) =~ dL(i)/C+w(i)
                  C


   Here, w(i) is a sample from a stochastic process W, which is a
   function of the capacity C, the current cross traffic X(i), and the
   current send bit rate R(i).  We model W as a white Gaussian process.
   If we are over-using the channel we expect w(i) to increase, and if a
   queue on the network path is being emptied, w(i) will decrease;
   otherwise the mean of w(i) will be zero.

   Breaking out the mean of w(i) to make it zero mean, we get

   Equation 5

     d(i) = dL(i)/C + m(i) + v(i)





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   This is our fundamental model, where we take into account that a
   large frame needs more time to traverse the link than a small frame,
   thus arriving with higher relative delay.  The noise term represents
   network jitter and other delay effects not captured by the model.

   When graphing the values for d(i) versus dL(i) on a scatterplot, we
   find that most samples cluster around the center, and the outliers
   are clustered along a line with average slope 1/C and zero offset.

   When using a regular video codec, most frames are roughly the same
   size after encoding (the central "cloud"); the exceptions are
   I-frames (or key frames) which are typically much larger than the
   average causing positive outliers (the I-frame itself) and negative
   outliers (the frame after an I-frame).

   The parameters d(i) and dL(i) are readily available for each frame i,
   and we want to estimate C and m(i) and use those estimates to detect
   whether or not we are over-using the bandwidth currently available.
   These parameters are easily estimated by any adaptive filter - we are
   using the Kalman filter.

   Let

     theta_bar(i) = [1/C(i) m(i)]^T

   and call it the state of time i.  We model the state evolution from
   time i to time i+1 as


     theta_bar(i+1) = theta_bar(i) + u_bar(i)

   where u_bar(i) is the zero mean white Gaussian process noise with
   covariance

   Equation 7

     Q(i) = E{u_bar(i) u_bar(i)^T}


   Given equation 5 we get

   Equation 8

     d(i) = h_bar(i)^T theta_bar(i) + v(i)

     h_bar(i) = [ dL(i) 1 ]^T





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   where v(i) is zero mean white Gaussian measurement noise with
   variance var_v = sigma(v,i)^2

   The Kalman filter recursively updates our estimate

     theta_hat(i) = [1/C_hat(i) m_hat(i)]^T

   as

     z(i) = d(i) - h_bar(i)^T * theta_hat(i-1)

     theta_hat(i) = theta_hat(i-1) + z(i) * k_bar(i)

                    E(i-1) * h_bar(i)
     k_bar(i) = ------------------------------
                  var_v_hat + h_bar(i)^T E(i-1)h_bar(i)

     E(i)=(I - K_bar(i) h_bar(i)^T) * E(i-1) + Q(i)

   I is the 2-by-2 identity matrix.

   The variance var_v = sigma(v,i)^2 is estimated using an exponential
   averaging filter, modified for variable sampling rate

     var_v_hat = beta*sigma(v,i-1)^2 + (1-beta)*z(i)^2

     beta = (1-alpha)30/(1000 * f_max)


   where f_max = max {1/(T(j) - T(j-1))} for j in i-K+1...i is the
   highest rate at which frames have been captured by the camera the
   last K frames and alpha is a filter coefficient typically chosen as a
   number in the interval [0.1, 0.001].  Since our assumption that v(i)
   should be zero mean WGN is less accurate in some cases, we have
   introduced an additional outlier filter around the updates of
   var_v_hat.  If z(i) > 3 var_v_hat the filter is updated with 3
   sqrt(var_v_hat) rather than z(i).  In a similar way, Q(i) is chosen
   as a diagonal matrix with main diagonal elements given by

     diag(Q(i)) = 30/(1000 * f_max)[10^-10 10^-2]^T

   It is necessary to scale these filter parameters with the frame rate
   to make the detector respond as quickly at low frame rates as at high
   frame rates.







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3.2.  Over-use detector

   The offset estimate m(i) is compared with a threshold gamma_1.  An
   estimate above the threshold is considered as an indication of over-
   use.  Such an indication is not enough for the detector to signal
   over-use to the rate control subsystem.  Not until over-use has been
   detected for at least gamma_2 milliseconds and at least gamma_3
   frames, a definitive over-use will be signaled.  However, if the
   offset estimate m(i) was decreased in the last update, over-use will
   not be signaled even if all the above conditions are met.  Similarly,
   the opposite state, under-use, is detected when m(i) < -gamma_1.  If
   neither over-use nor under-use is detected, the detector will be in
   the normal state.

3.3.  Rate control

   The rate control at the receiving side is designed to increase the
   available bandwidth estimate A_hat as long as the detected state is
   normal.  Doing that assures that we, sooner or later, will reach the
   available bandwidth of the channel and detect an over-use.

   As soon as over-use has been detected the available bandwidth
   estimate is decreased.  In this way we get a recursive and adaptive
   estimate of the available bandwidth.

   In this design description we make the assumption that the rate
   control subsystem is executed periodically and that this period is
   constant.

   The rate control subsystem has 3 states: Increase, Decrease and Hold.
   "Increase" is the state when no congestion is detected; "Decrease" is
   the state where congestion is detected, and "Hold" is a state that
   waits until built-up queues have drained before going to "increase"
   state.

   The state transitions (with blank fields meaning "remain in state")
   are:

   State ---->  | Hold      |Increase    |Decrease
   Signal-----------------------------------------
     v          |           |            |
   Over-use     | Decrease  |Decrease    |
   -----------------------------------------------
   Normal       | Increase  |            |Hold
   -----------------------------------------------
   Under-use    |           |Hold        |Hold
   -----------------------------------------------




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   The subsystem starts in the increase state, where it will stay until
   over-use or under-use has been detected by the detector subsystem.
   On every update the available bandwidth is increased with a factor
   which is a function of the global system response time and the
   estimated measurement noise variance var_v_hat.  The global system
   response time is the time from an increase that causes over-use until
   that over-use can be detected by the over-use detector.  The variance
   var_v_hat affects how responsive the Kalman filter is, and is thus
   used as an indicator of the delay inflicted by the Kalman filter.

     A(i) = eta*A(i-1)
                                    1.001+B
     eta(RTT, var_v_hat) = ------------------------------------------
                              1+e^(b(d*RTT - (c1 * var_v_hat + c2)))

   Here, B, b, d, c1 and c2 are design parameters.

   Since the system depends on over-using the channel to verify the
   current available bandwidth estimate, we must make sure that our
   estimate doesn't diverge from the rate at which the sender is
   actually sending.  Thus, if the sender is unable to produce a bit
   stream with the bit rate the receiver is asking for, the available
   bandwidth estimate must stay within a given bound.  Therefore we
   introduce a threshold

     A_hat(i) < 1.5 * R_hat(i)

   where R_hat(i) is the incoming bit rate measured over a T seconds
   window:

     R_hat(i) = 1/T * sum(L(j)) for j from 1 to N(i)

   N(i) is the number of frames received the past T seconds and L(j) is
   the payload size of frame j.

   When an over-use is detected the system transitions to the decrease
   state, where the available bandwidth estimate is decreased to a
   factor times the currently incoming bit rate.

     A_hat(i) = alpha*R_hat(i)

   alpha is typically chosen to be in the interval [0.8, 0.95].

   When the detector signals under-use to the rate control subsystem, we
   know that queues in the network path are being emptied, indicating
   that our available bandwidth estimate is lower than the actual
   available bandwidth.  Upon that signal the rate control subsystem
   will enter the hold state, where the available bandwidth estimate



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   will be held constant while waiting for the queues to stabilize at a
   lower level - a way of keeping the delay as low as possible.  This
   decrease of delay is wanted, and expected, immediately after the
   estimate has been reduced due to over-use, but can also happen if the
   cross traffic over some links is reduced.  In either case we want to
   measure the highest incoming rate during the under-use interval:

     R_max = max{R_hat(i)} for i in 1..K


   where K is the number of frames of under-use before returning to the
   normal state.  R_max is a measure of the actual bandwidth available
   and is a good guess of what bit rate we should be able to transmit
   at.  Therefore the available bandwidth will be set to Rmax when we
   transition from the hold state to the increase state.


4.  Sender side control

   An additional congestion controller resides at the sending side.  It
   bases its decisions on the round-trip time, packet loss and available
   bandwidth estimates transmitted from the receiving side.

   The available bandwidth estimates produced by the receiving side are
   only reliable when the size of the queues along the channel are large
   enough.  If the queues are very short, over-use will only be visible
   through packet losses, which aren't used by the receiving side
   algorithm.

   This algorithm is run every time a receive report arrives at the
   sender, which will happen [[how often do we expect? and why?]].  If
   no receive report is recieved within [[what timeout?]], the algorithm
   will take action as if all packets in the interval have been lost.
   [[does that make sense?]]

   o  If 2-10% of the packets have been lost since the previous report
      from the receiver, the sender available bandwidth estimate As(i)
      (As denotes 'sender available bandwidth') will be kept unchanged.

   o  If more than 10% of the packets have been lost a new estimate is
      calculated as As(i)=As(i-1)(1-0.5p), where p is the loss ratio.

   o  As long as less than 2% of the packets have been lost As(i) will
      be increased as As(i)=1.05(As(i-1)+1000)

   The new send-side estimate is limited by the TCP Friendly Rate
   Control formula [RFC3448] and the receive-side estimate of the
   available bandwidth A(i):



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                                  8 s
   As(i) >= ----------------------------------------------------------
            R*sqrt(2*b*p/3) + (t_RTO*(3*sqrt(3*b*p/8) * p * (1+32*p^2)))

   As(i) <= A(i)


   where b is the number of packets acknowledged by a single TCP
   acknowledgement (set to 1 per TFRC recommendations), t_RTO is the TCP
   retransmission timeout value in seconds (set to 4*R) and s is the
   average packet size in bytes.

   (The multiplication by 8 comes because TFRC is computing bandwidth in
   bytes, while this document computes bandwidth in bits.)

   In words: The sender-side estimate will never be larger than the
   receiver-side estimate, and will never be lower than the estimate
   from the TFRC formula.

   We motivate the packet loss thresholds by noting that if we have
   small amount of packet losses due to over-use, that amount will soon
   increase if we don't adjust our bit rate.  Therefore we will soon
   enough reach above the 10 % threshold and adjust As(i).  However if
   the packet loss rate does not increase, the losses are probably not
   related to self-induced channel over-use and therefore we should not
   react on them.


5.  Interoperability Considerations

   There are three scenarios of interest, and one included for reference

   o  Both parties implement the algorithms described here

   o  Sender implements the algorithm described in section Section 4,
      recipient does not implement Section 3

   o  Recipient implements the algorithm in section Section 3, sender
      does not implement Section 4.

   In the case where both parties implement the algorithms, we expect to
   see most of the congestion control response to slowly varying
   conditions happen by TMMBR messages from recipient to sender.  At
   most times, the sender will send less than the congestion-inducing
   bandwidth limit C, and when he sends more, congestion will be
   detected before packets are lost.

   If sudden changes happen, packets will be lost, and the sender side



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   control will trigger, limiting traffic until the congestion becomes
   low enough that the system switches back to the receiver-controlled
   state.

   In the case where sender only implements, we expect to see somewhat
   higher loss rates and delays, but the system will still be overall
   TCP friendly and self-adjusting; the governing term in the
   calculation will be the TFRC formula.

   In the case where recipient implements this algorithm and sender does
   not, congestion will be avoided for slow changes as long as the
   sender understands and obeys TMMBR; there will be no backoff for
   packet-loss-inducing changes in capacity.  Given that some kind of
   congestion control is mandatory for the sender according to the TMMBR
   spec, this case has to be reevaluated against the specific congestion
   control implemented by the sender.


6.  Implementation Experience

   This algorithm has been implemented in the open-source WebRTC
   project.


7.  Further Work

   This draft is offered as input to the congestion control discussion.

   Work that can be done on this basis includes:

   o  Consideration of timing info: It may be sensible to use the
      proposed TFRC RTP header extensions
      [I-D.gharai-avtcore-rtp-tfrc]to carry per-packet timing
      information, which would both give more data points and a
      timestamp applied closer to the network interface.

   o  Considerations of cross-channel calculation: If all packets in
      multiple streams follow the same path over the network, congestion
      or queueing information should be considered across all packets
      between two parties, not just per media stream.

   o  Considerations of cross-channel balancing: The decision to slow
      down sending in a situation with multiple media streams should be
      taken across all media streams, not per stream.

   o  Considerations of additional input: How and where packet loss
      detected at the recipient can be added to the algorithm.




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   o  Considerations of locus of control: Whether the sender or the
      recipient is in the best position to figure out which media
      streams it makes sense to slow down, and therefore whether one
      should use TMMBR to slow down one channel, signal an overall
      bandwidth change and let the sender make the decision, or signal
      the (possibly processed) delay info and let the sender run the
      algorithm.

   These are matters for further work; since some of them involve
   extensions that have not yet been standardized, this could take some
   time, and it's important to consider when this work can be completed.


8.  IANA Considerations

   This document makes no request of IANA.

   Note to RFC Editor: this section may be removed on publication as an
   RFC.


9.  Security Considerations

   An attacker with the ability to insert or remove messages on the
   connection will, of course, have the ability to mess up rate control,
   causing people to send either too fast or too slow, and causing
   congestion.

   In this case, the control information is carried inside RTP, and can
   be protected against modification or message insertion using SRTP,
   just as for the media.  Given that timestamps are carried in the RTP
   header, which is not encrypted, this is not protected against
   disclosure, but it seems hard to mount an attack based on timing
   information only.


10.  Acknowledgements


11.  References

11.1.  Normative References

   [RFC2119]  Bradner, S., "Key words for use in RFCs to Indicate
              Requirement Levels", BCP 14, RFC 2119, March 1997.

   [RFC3448]  Handley, M., Floyd, S., Padhye, J., and J. Widmer, "TCP
              Friendly Rate Control (TFRC): Protocol Specification",



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              RFC 3448, January 2003.

   [RFC3550]  Schulzrinne, H., Casner, S., Frederick, R., and V.
              Jacobson, "RTP: A Transport Protocol for Real-Time
              Applications", STD 64, RFC 3550, July 2003.

   [RFC5104]  Wenger, S., Chandra, U., Westerlund, M., and B. Burman,
              "Codec Control Messages in the RTP Audio-Visual Profile
              with Feedback (AVPF)", RFC 5104, February 2008.

11.2.  Informative References

   [I-D.gharai-avtcore-rtp-tfrc]
              Gharai, L. and C. Perkins, "RTP with TCP Friendly Rate
              Control", draft-gharai-avtcore-rtp-tfrc-00 (work in
              progress), March 2011.

   [RFC2914]  Floyd, S., "Congestion Control Principles", BCP 41,
              RFC 2914, September 2000.


Authors' Addresses

   Henrik Lundin
   Google
   Kungsbron 2
   Stockholm  11122
   Sweden


   Stefan Holmer
   Google
   Kungsbron 2
   Stockholm  11122
   Sweden

   Email: holmer@google.com


   Harald Alvestrand (editor)
   Google
   Kungsbron 2
   Stockholm  11122
   Sweden

   Email: harald@alvestrand.no





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