Network Working Group                                          S. Holmer
Internet-Draft                                                 H. Lundin
Intended status: Informational                                    Google
Expires: January 9, 2017                                     G. Carlucci
                                                             L. De Cicco
                                                              S. Mascolo
                                                     Politecnico di Bari
                                                            July 8, 2016

   A Google Congestion Control Algorithm for Real-Time Communication


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

   It is published as an input document to the RMCAT working group on
   congestion control for media streams.  The mailing list of that
   working group is

Requirements Language

   The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT",
   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

   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 January 9, 2017.

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Copyright Notice

   Copyright (c) 2016 IETF Trust and the persons identified as the
   document authors.  All rights reserved.

   This document is subject to BCP 78 and the IETF Trust's Legal
   Provisions Relating to IETF Documents
   ( 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.  Mathematical notation conventions . . . . . . . . . . . .   3
   2.  System model  . . . . . . . . . . . . . . . . . . . . . . . .   4
   3.  Feedback and extensions . . . . . . . . . . . . . . . . . . .   4
   4.  Sending Engine  . . . . . . . . . . . . . . . . . . . . . . .   5
   5.  Delay-based control . . . . . . . . . . . . . . . . . . . . .   5
     5.1.  Arrival-time model  . . . . . . . . . . . . . . . . . . .   6
     5.2.  Pre-filtering . . . . . . . . . . . . . . . . . . . . . .   7
     5.3.  Arrival-time filter . . . . . . . . . . . . . . . . . . .   7
     5.4.  Over-use detector . . . . . . . . . . . . . . . . . . . .   8
     5.5.  Rate control  . . . . . . . . . . . . . . . . . . . . . .  10
     5.6.  Parameters settings . . . . . . . . . . . . . . . . . . .  12
   6.  Loss-based control  . . . . . . . . . . . . . . . . . . . . .  13
   7.  Interoperability Considerations . . . . . . . . . . . . . . .  14
   8.  Implementation Experience . . . . . . . . . . . . . . . . . .  14
   9.  Further Work  . . . . . . . . . . . . . . . . . . . . . . . .  15
   10. IANA Considerations . . . . . . . . . . . . . . . . . . . . .  15
   11. Security Considerations . . . . . . . . . . . . . . . . . . .  15
   12. Acknowledgements  . . . . . . . . . . . . . . . . . . . . . .  15
   13. References  . . . . . . . . . . . . . . . . . . . . . . . . .  16
     13.1.  Normative References . . . . . . . . . . . . . . . . . .  16
     13.2.  Informative References . . . . . . . . . . . . . . . . .  16
   Appendix A.  Change log . . . . . . . . . . . . . . . . . . . . .  16
     A.1.  Version -00 to -01  . . . . . . . . . . . . . . . . . . .  16
     A.2.  Version -01 to -02  . . . . . . . . . . . . . . . . . . .  17
     A.3.  Version -02 to -03  . . . . . . . . . . . . . . . . . . .  17
     A.4.  rtcweb-03 to rmcat-00 . . . . . . . . . . . . . . . . . .  17
     A.5.  rmcat -00 to -01  . . . . . . . . . . . . . . . . . . . .  17
     A.6.  rmcat -01 to -02  . . . . . . . . . . . . . . . . . . . .  17
     A.7.  rmcat -02 to -03  . . . . . . . . . . . . . . . . . . . .  18
     A.8.  ietf-rmcat -00 to ietf-rmcat -01  . . . . . . . . . . . .  18

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     A.9.  ietf-rmcat -01 to ietf-rmcat -02  . . . . . . . . . . . .  18
   Authors' Addresses  . . . . . . . . . . . . . . . . . . . . . . .  18

1.  Introduction

   Congestion control is a requirement for all applications sharing the
   Internet resources [RFC2914].

   Congestion control for real-time media is challenging for a number of

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

   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

   This memo describes two congestion control algorithms that together
   are able to provide good performance and reasonable bandwidth sharing
   with other video flows using the same congestion control and with TCP
   flows that share the same links.

   The signaling used consists of experimental RTP header extensions and
   RTCP messages RFC 3550 [RFC3550] as defined in [abs-send-time],
   [I-D.alvestrand-rmcat-remb] and

1.1.  Mathematical notation conventions

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

   The following notational conventions are used:

   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 vector X - conventionally marked by a
      subscript i.

   E{X}  The expected value of the stochastic variable X

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2.  System model

   The following elements are in the system:

   o  RTP packet - an RTP packet containing media data.

   o  Group of packets - a set of RTP packets transmitted from the
      sender uniquely identified by the group departure and group
      arrival time (absolute send time) [abs-send-time].  These could be
      video packets, audio packets, or a mix of audio and video packets.

   o  Incoming media stream - a stream of frames consisting of RTP

   o  RTP sender - sends the RTP stream over the network to the RTP
      receiver.  It generates the RTP timestamp and the abs-send-time
      header extension

   o  RTP receiver - receives the RTP stream, marks the time of arrival.

   o  RTCP sender at RTP receiver - sends receiver reports, REMB
      messages and transport-wide RTCP feedback messages.

   o  RTCP receiver at RTP sender - receives receiver reports and REMB
      messages and transport-wide RTCP feedback messages, reports these
      to the sender side controller.

   o  RTCP receiver at RTP receiver, receives sender reports from the

   o  Loss-based controller - takes loss rate measurement, round trip
      time measurement and REMB messages, and computes a target sending

   o  Delay-based controller - takes the packet arrival info, either at
      the RTP receiver, or from the feedback received by the RTP sender,
      and computes a maximum bitrate which it passes to the loss-based

   Together, loss-based controller and delay-based controller implement
   the congestion control algorithm.

3.  Feedback and extensions

   There are two ways to implement the proposed algorithm.  One where
   both the controllers are running at the send-side, and one where the
   delay-based controller runs on the receive-side and the loss-based
   controller runs on the send-side.

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   The first version can be realized by using a per-packet feedback
   protocol as described in
   [I-D.holmer-rmcat-transport-wide-cc-extensions].  Here, the RTP
   receiver will record the arrival time and the transport-wide sequence
   number of each received packet, which will be sent back to the sender
   periodically using the transport-wide feedback message.  The
   RECOMMENDED feedback interval is once per received video frame or at
   least once every 30 ms if audio-only or multi-stream.  If the
   feedback overhead needs to be limited this interval can be increased
   to 100 ms.

   The sender will map the received {sequence number, arrival time}
   pairs to the send-time of each packet covered by the feedback report,
   and feed those timestamps to the delay-based controller.  It will
   also compute a loss ratio based on the sequence numbers in the
   feedback message.

   The second version can be realized by having a delay-based controller
   at the receive-side, monitoring and processing the arrival time and
   size of incoming packets.  The sender SHOULD use the abs-send-time
   RTP header extension [abs-send-time] to enable the receiver to
   compute the inter-group delay variation.  The output from the delay-
   based controller will be a bitrate, which will be sent back to the
   sender using the REMB feedback message [I-D.alvestrand-rmcat-remb].
   The packet loss ratio is sent back via RTCP receiver reports.  At the
   sender the bitrate in the REMB message and the fraction of packets
   lost are fed into the loss-based controller, which outputs a final
   target bitrate.  It is RECOMMENDED to send the REMB message as soon
   as congestion is detected, and otherwise at least once every second.

4.  Sending Engine

   Pacing is used to actuate the target bitrate computed by the

   When media encoder produces data, this is fed into a Pacer queue.
   The Pacer sends a group of packets to the network every burst_time
   interval.  RECOMMENDED value for burst_time is 5 ms.  The size of a
   group of packets is computed as the product between the target
   bitrate and the burst_time.

5.  Delay-based control

   The delay-based control algorithm can be further decomposed into four
   parts: a pre-filtering, an arrival-time filter, an over-use detector,
   and a rate controller.

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5.1.  Arrival-time model

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

   We define the inter-arrival time, t(i) - t(i-1), as the difference in
   arrival time of two groups of packets.  Correspondingly, the inter-
   departure time, T(i) - T(i-1), is defined as the difference in
   departure-time of two groups of packets.  Finally, the inter-group
   delay variation, d(i), is defined as the difference between the
   inter-arrival time and the inter-departure time.  Or interpreted
   differently, as the difference between the delay of group i and group

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

   An inter-departure time is computed between consecutive groups as
   T(i) - T(i-1), where T(i) is the departure timestamp of the last
   packet in the current packet group being processed.  Any packets
   received out of order are ignored by the arrival-time model.

   Each group is assigned a receive time t(i), which corresponds to the
   time at which the last packet of the group was received.  A group is
   delayed relative to its predecessor if t(i) - t(i-1) > T(i) - T(i-1),
   i.e., if the inter-arrival time is larger than the inter-departure

   We can model the inter-group delay variation as:

     d(i) = w(i)

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

   Breaking out the mean, m(i), from w(i) to make the process zero mean,
   we get

   Equation 1

     d(i) = m(i) + v(i)

   The noise term v(i) represents network jitter and other delay effects
   not captured by the model.

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5.2.  Pre-filtering

   The pre-filtering aims at handling delay transients caused by channel
   outages.  During an outage, packets being queued in network buffers,
   for reasons unrelated to congestion, are delivered in a burst when
   the outage ends.

   The pre-filtering merges together groups of packets that arrive in a
   burst.  Packets are merged in the same group if one of these two
   conditions holds:

   o  A sequence of packets which are sent within a burst_time interval
      constitute a group.

   o  A Packet which has an inter-arrival time less than burst_time and
      an inter-group delay variation d(i) less than 0 is considered
      being part of the current group of packets.

5.3.  Arrival-time filter

   The parameter d(i) is readily available for each group of packets, i
   > 1.  We want to estimate m(i) and use this estimate to detect
   whether or not the bottleneck link is over-used.  The parameter can
   be estimated by any adaptive filter - we are using the Kalman filter.

   Let m(i) be the estimate at time i

   We model the state evolution from time i to time i+1 as

     m(i+1) = m(i) + u(i)

   where u(i) is the state noise that we model as a stationary process
   with Gaussian statistic with zero mean and variance

     q(i) = E{u(i)^2}

   q(i) is RECOMMENDED equal to 10^-3

   Given equation 1 we get

       d(i) = m(i) + v(i)

   where v(i) is zero mean white Gaussian measurement noise with
   variance var_v = E{v(i)^2}

   The Kalman filter recursively updates our estimate m_hat(i) as

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     z(i) = d(i) - m_hat(i-1)

     m_hat(i) = m_hat(i-1) + z(i) * k(i)

                        e(i-1) + q(i)
     k(i) = ----------------------------------------
                var_v_hat(i) + (e(i-1) + q(i))

     e(i) = (1 - k(i)) * (e(i-1) + q(i))

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

     var_v_hat(i) = max(alpha * var_v_hat(i-1) + (1-alpha) * z(i)^2, 1)

     alpha = (1-chi)^(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 the last K packet groups have been received and
   chi 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*sqrt(var_v_hat) the filter is updated with 3*sqrt(var_v_hat) rather
   than z(i).  For instance v(i) will not be white in situations where
   packets are sent at a higher rate than the channel capacity, in which
   case they will be queued behind each other.

5.4.  Over-use detector

   The inter-group delay variation estimate m(i), obtained as the output
   of the arrival-time filter, is compared with a threshold
   del_var_th(i).  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.  A
   definitive over-use will be signaled only if over-use has been
   detected for at least overuse_time_th milliseconds.  However, if m(i)
   < m(i-1), 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) < -del_var_th(i).  If neither over-use nor under-
   use is detected, the detector will be in the normal state.

   The threshold del_var_th has a remarkable impact on the overall
   dynamics and performance of the algorithm.  In particular, it has
   been shown that using a static threshold del_var_th, a flow
   controlled by the proposed algorithm can be starved by a concurrent
   TCP flow [Pv13].  This starvation can be avoided by increasing the
   threshold del_var_th to a sufficiently large value.

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   The reason is that, by using a larger value of del_var_th, a larger
   queuing delay can be tolerated, whereas with a small del_var_th, the
   over-use detector quickly reacts to a small increase in the offset
   estimate m(i) by generating an over-use signal that reduces the
   delay-based estimate of the available bandwidth A_hat (see
   Section 4.4).  Thus, it is necessary to dynamically tune the
   threshold del_var_th to get good performance in the most common
   scenarios, such as when competing with loss-based flows.

   For this reason, we propose to vary the threshold del_var_th(i)
   according to the following dynamic equation:

del_var_th(i) =
         del_var_th(i-1) + (t(i)-t(i-1)) * K(i) * (|m(i)|-del_var_th(i-1))

   with K(i)=K_d if |m(i)| < del_var_th(i-1) or K(i)=K_u otherwise.  The
   rationale is to increase del_var_th(i) when m(i) is outside of the
   range [-del_var_th(i-1),del_var_th(i-1)], whereas, when the offset
   estimate m(i) falls back into the range, del_var_th is decreased.  In
   this way when m(i) increases, for instance due to a TCP flow entering
   the same bottleneck, del_var_th(i) increases and avoids the
   uncontrolled generation of over-use signals which may lead to
   starvation of the flow controlled by the proposed algorithm [Pv13].
   Moreover, del_var_th(i) SHOULD NOT be updated if this condition

     |m(i)| - del_var_th(i) > 15

   It is also RECOMMENDED to clamp del_var_th(i) to the range [6, 600],
   since a too small del_var_th(i) can cause the detector to become
   overly sensitive.

   On the other hand, when m(i) falls back into the range
   [-del_var_th(i-1),del_var_th(i-1)] the threshold del_var_th(i) is
   decreased so that a lower queuing delay can be achieved.

   It is RECOMMENDED to choose K_u > K_d so that the rate at which
   del_var_th is increased is higher than the rate at which it is
   decreased.  With this setting it is possible to increase the
   threshold in the case of a concurrent TCP flow and prevent starvation
   as well as enforcing intra-protocol fairness.  RECOMMENDED values for
   del_var_th(0), overuse_time_th, K_u and K_d are respectively 12.5 ms,
   10 ms, 0.01 and 0.00018.

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5.5.  Rate control

   The rate control is split in two parts, one controlling the bandwidth
   estimate based on delay, and one controlling the bandwidth estimate
   based on loss.  Both are designed to increase the estimate of the
   available bandwidth A_hat as long as there is no detected congestion
   and to ensure that we will eventually match the available bandwidth
   of the channel and detect an over-use.

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

   In this document 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"

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

   |     \ State |   Hold    |  Increase  |Decrease|
   |      \      |           |            |        |
   | Signal\     |           |            |        |
   |  Over-use   | Decrease  |  Decrease  |        |
   |  Normal     | Increase  |            |  Hold  |
   |  Under-use  |           |   Hold     |  Hold  |

   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 delay-based estimate of the available bandwidth
   is increased, either multiplicatively or additively, depending on its
   current state.

   The system does a multiplicative increase if the current bandwidth
   estimate appears to be far from convergence, while it does an
   additive increase if it appears to be closer to convergence.  We
   assume that we are close to convergence if the currently incoming
   bitrate, R_hat(i), is close to an average of the incoming bitrates at

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   the time when we previously have been in the Decrease state.  "Close"
   is defined as three standard deviations around this average.  It is
   RECOMMENDED to measure this average and standard deviation with an
   exponential moving average with the smoothing factor 0.95, as it is
   expected that this average covers multiple occasions at which we are
   in the Decrease state.  Whenever valid estimates of these statistics
   are not available, we assume that we have not yet come close to
   convergence and therefore remain in the multiplicative increase

   If R_hat(i) increases above three standard deviations of the average
   max bitrate, we assume that the current congestion level has changed,
   at which point we reset the average max bitrate and go back to the
   multiplicative increase state.

   R_hat(i) is the incoming bitrate measured by the delay-based
   controller 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 packets received the past T seconds and L(j) is
   the payload size of packet j.  A window between 0.5 and 1 second is

   During multiplicative increase, the estimate is increased by at most
   8% per second.

     eta = 1.08^min(time_since_last_update_ms / 1000, 1.0)
     A_hat(i) = eta * A_hat(i-1)

   During the additive increase the estimate is increased with at most
   half a packet per response_time interval.  The response_time interval
   is estimated as the round-trip time plus 100 ms as an estimate of
   over-use estimator and detector reaction time.

    response_time_ms = 100 + rtt_ms
    alpha = 0.5 * min(time_since_last_update_ms / response_time_ms, 1.0)
    A_hat(i) = A_hat(i-1) + max(1000, alpha * expected_packet_size_bits)

   expected_packet_size_bits is used to get a slightly slower slope for
   the additive increase at lower bitrates.  It can for instance be
   computed from the current bitrate by assuming a frame rate of 30
   frames per second:

     bits_per_frame = A_hat(i-1) / 30
     packets_per_frame = ceil(bits_per_frame / (1200 * 8))
     avg_packet_size_bits = bits_per_frame / packets_per_frame

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

     A_hat(i) < 1.5 * R_hat(i)

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

     A_hat(i) = beta * R_hat(i)

   beta is typically chosen to be in the interval [0.8, 0.95], 0.85 is
   the RECOMMENDED value.

   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 A_hat is lower than the actual
   available bandwidth.  Upon that signal the rate control subsystem
   will enter the hold state, where the receive-side available bandwidth
   estimate 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.

   It is RECOMMENDED that the routine to update A_hat(i) is run at least
   once every response_time interval.

5.6.  Parameters settings

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   | Parameter       | Description                       | RECOMMENDED |
   |                 |                                   | Value       |
   | burst_time      | Time limit in milliseconds        | 5 ms        |
   |                 | between packet bursts which       |             |
   |                 | identifies a group                |             |
   | q               | State noise covariance matrix     | q = 10^-3   |
   | e(0)            | Initial value of the  system      | e(0) = 0.1  |
   |                 | error covariance                  |             |
   | chi             | Coefficient used  for the         | [0.1,       |
   |                 | measured noise variance           | 0.001]      |
   | del_var_th(0)   | Initial value for the adaptive    | 12.5 ms     |
   |                 | threshold                         |             |
   | overuse_time_th | Time required to trigger an       | 10 ms       |
   |                 | overuse signal                    |             |
   | K_u             | Coefficient for the adaptive      | 0.01        |
   |                 | threshold                         |             |
   | K_d             | Coefficient for the adaptive      | 0.00018     |
   |                 | threshold                         |             |
   | T               | Time window for measuring the     | [0.5, 1] s  |
   |                 | received bitrate                  |             |
   | beta            | Decrease rate factor              | 0.85        |

          Table 1: RECOMMENDED values for delay based controller

                                  Table 1

6.  Loss-based control

   A second part of the congestion controller bases its decisions on the
   round-trip time, packet loss and available bandwidth estimates A_hat
   received from the delay-based controller.  The available bandwidth
   estimates computed by the loss-based controller are denoted with

   The available bandwidth estimates A_hat produced by the delay-based
   controller are only reliable when the size of the queues along the
   path sufficiently large.  If the queues are very short, over-use will
   only be visible through packet losses, which are not used by the
   delay-based controller.

   The loss-based controller SHOULD run every time feedback from the
   receiver is received.

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

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

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

   The loss-based estimate As_hat is compared with the delay-based
   estimate A_hat.  The actual sending rate is set as the minimum
   between As_hat and A_hat.

   We motivate the packet loss thresholds by noting that if the
   transmission channel has a small amount of packet loss due to over-
   use, that amount will soon increase if the sender does not adjust his
   bitrate.  Therefore we will soon enough reach above the 10% threshold
   and adjust As_hat(i).  However, if the packet loss ratio does not
   increase, the losses are probably not related to self-inflicted
   congestion and therefore we should not react on them.

7.  Interoperability Considerations

   In case a sender implementing these algorithms talks to a receiver
   which do not implement any of the proposed RTCP messages and RTP
   header extensions, it is suggested that the sender monitors RTCP
   receiver reports and uses the fraction of lost packets and the round-
   trip time as input to the loss-based controller.  The delay-based
   controller should be left disabled.

8.  Implementation Experience

   This algorithm has been implemented in the open-source WebRTC
   project, has been in use in Chrome since M23, and is being used by
   Google Hangouts.

   Deployment of the algorithm have revealed problems related to, e.g,
   congested or otherwise problematic WiFi networks, which have led to
   algorithm improvements.  The algorithm has also been tested in a
   multi-party conference scenario with a conference server which
   terminates the congestion control between endpoints.  This ensures
   that no assumptions are being made by the congestion control about
   maximum send and receive bitrates, etc., which typically is out of
   control for a conference server.

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9.  Further Work

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

   Work that can be done on this basis includes:

   o  Considerations of integrated loss control: How loss and delay
      control can be better integrated, and the loss control improved.

   o  Considerations of locus of control: evaluate the performance of
      having all congestion control logic at the sender, compared to
      splitting logic between sender and receiver.

   o  Considerations of utilizing ECN as a signal for congestion
      estimation and link over-use detection.

10.  IANA Considerations

   This document makes no request of IANA.

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

11.  Security Considerations

   An attacker with the ability to insert or remove messages on the
   connection would have the ability to disrupt rate control.  This
   could make the algorithm to produce either a sending rate under-
   utilizing the bottleneck link capacity, or a too high sending rate
   causing network 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.

12.  Acknowledgements

   Thanks to Randell Jesup, Magnus Westerlund, Varun Singh, Tim Panton,
   Soo-Hyun Choo, Jim Gettys, Ingemar Johansson, Michael Welzl and
   others for providing valuable feedback on earlier versions of this

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13.  References

13.1.  Normative References

              Alvestrand, H., "RTCP message for Receiver Estimated
              Maximum Bitrate", draft-alvestrand-rmcat-remb-03 (work in
              progress), October 2013.

              Holmer, S., Flodman, M., and E. Sprang, "RTP Extensions
              for Transport-wide Congestion Control", draft-holmer-
              rmcat-transport-wide-cc-extensions-00 (work in progress),
              March 2015.

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

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

              "RTP Header Extension for Absolute Sender Time",

13.2.  Informative References

   [Pv13]     De Cicco, L., Carlucci, G., and S. Mascolo, "Understanding
              the Dynamic Behaviour of the Google Congestion Control",
              Packet Video Workshop , December 2013.

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

Appendix A.  Change log

A.1.  Version -00 to -01

   o  Added change log

   o  Added appendix outlining new extensions

   o  Added a section on when to send feedback to the end of section 3.3
      "Rate control", and defined min/max FB intervals.

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   o  Added size of over-bandwidth estimate usage to "further work"

   o  Added startup considerations to "further work" section.

   o  Added sender-delay considerations to "further work" section.

   o  Filled in acknowledgments section from mailing list discussion.

A.2.  Version -01 to -02

   o  Defined the term "frame", incorporating the transmission time
      offset into its definition, and removed references to "video

   o  Referred to "m(i)" from the text to make the derivation clearer.

   o  Made it clearer that we modify our estimates of available
      bandwidth, and not the true available bandwidth.

   o  Removed the appendixes outlining new extensions, added pointers to
      REMB draft and RFC 5450.

A.3.  Version -02 to -03

   o  Added a section on how to process multiple streams in a single
      estimator using RTP timestamps to NTP time conversion.

   o  Stated in introduction that the draft is aimed at the RMCAT
      working group.

A.4.  rtcweb-03 to rmcat-00

   Renamed draft to link the draft name to the RMCAT WG.

A.5.  rmcat -00 to -01

   Spellcheck.  Otherwise no changes, this is a "keepalive" release.

A.6.  rmcat -01 to -02

   o  Added Luca De Cicco and Saverio Mascolo as authors.

   o  Extended the "Over-use detector" section with new technical
      details on how to dynamically tune the offset del_var_th for
      improved fairness properties.

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   o  Added reference to a paper analyzing the behavior of the proposed

A.7.  rmcat -02 to -03

   o  Swapped receiver-side/sender-side controller with delay-based/
      loss-based controller as there is no longer a requirement to run
      the delay-based controller on the receiver-side.

   o  Removed the discussion about multiple streams and transmission
      time offsets.

   o  Introduced a new section about "Feedback and extensions".

   o  Improvements to the threshold adaptation in the "Over-use
      detector" section.

   o  Swapped the previous MIMD rate control algorithm for a new AIMD
      rate control algorithm.

A.8.  ietf-rmcat -00 to ietf-rmcat -01

   o  Arrival-time filter converted from a two dimensional Kalman filter
      to a scalar Kalman filter.

   o  The use of the TFRC equation was removed from the loss-based
      controller, as it turned out to have little to no effect in

A.9.  ietf-rmcat -01 to ietf-rmcat -02

   o  Added a section which better describes the pre-filtering

Authors' Addresses

   Stefan Holmer
   Kungsbron 2
   Stockholm  11122


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   Henrik Lundin
   Kungsbron 2
   Stockholm  11122


   Gaetano Carlucci
   Politecnico di Bari
   Via Orabona, 4
   Bari  70125


   Luca De Cicco
   Politecnico di Bari
   Via Orabona, 4
   Bari  70125


   Saverio Mascolo
   Politecnico di Bari
   Via Orabona, 4
   Bari  70125


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