RMCAT WG                                                    I. Johansson
Internet-Draft                                                 Z. Sarker
Intended status: Experimental                                Ericsson AB
Expires: April 21, 2016                                 October 19, 2015

              Self-Clocked Rate Adaptation for Multimedia


   This memo describes a rate adaptation algorithm for conversational
   media services such as video.  The solution conforms to the packet
   conservation principle and uses a hybrid loss and delay based
   congestion control algorithm.  The algorithm is evaluated over both
   simulated Internet bottleneck scenarios as well as in a LTE (Long
   Term Evolution) system simulator and is shown to achieve both low
   latency and high video throughput in these scenarios.

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 April 21, 2016.

Copyright Notice

   Copyright (c) 2015 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
   (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

Johansson & Sarker       Expires April 21, 2016                 [Page 1]

Internet-Draft                   SCReAM                     October 2015

   the Trust Legal Provisions and are provided without warranty as
   described in the Simplified BSD License.

Table of Contents

   1.  Introduction  . . . . . . . . . . . . . . . . . . . . . . . .   3
     1.1.  Wireless (LTE) access properties  . . . . . . . . . . . .   3
     1.2.  Why is it a self-clocked algorithm? . . . . . . . . . . .   3
   2.  Terminology . . . . . . . . . . . . . . . . . . . . . . . . .   4
   3.  Overview of SCReAM Algorithm  . . . . . . . . . . . . . . . .   4
     3.1.  Network Congestion Control  . . . . . . . . . . . . . . .   7
     3.2.  Sender Transmission Control . . . . . . . . . . . . . . .   7
     3.3.  Media Rate Control  . . . . . . . . . . . . . . . . . . .   7
   4.  Detailed Description of SCReAM  . . . . . . . . . . . . . . .   8
     4.1.  SCReAM Sender . . . . . . . . . . . . . . . . . . . . . .   8
       4.1.1.  Constants and Parameter values  . . . . . . . . . . .   8  Constants . . . . . . . . . . . . . . . . . . . .   8  State variables . . . . . . . . . . . . . . . . .  10
       4.1.2.  Network congestion control  . . . . . . . . . . . . .  11  Updating bytes_newly_acked  . . . . . . . . . . .  14  Updating congestion window  . . . . . . . . . . .  14  Compensation for competing flows  . . . . . . . .  16  Send window calculation . . . . . . . . . . . . .  17  Resuming fast increase  . . . . . . . . . . . . .  18
       4.1.3.  Media rate control  . . . . . . . . . . . . . . . . .  18  FEC and packet overhead considerations  . . . . .  22
     4.2.  SCReAM Receiver . . . . . . . . . . . . . . . . . . . . .  22
   5.  Discussion  . . . . . . . . . . . . . . . . . . . . . . . . .  22
   6.  Implementation status . . . . . . . . . . . . . . . . . . . .  23
     6.1.  OpenWebRTC  . . . . . . . . . . . . . . . . . . . . . . .  23
     6.2.  A C++ Implementation of SCReAM  . . . . . . . . . . . . .  24
   7.  Acknowledgements  . . . . . . . . . . . . . . . . . . . . . .  24
   8.  IANA Considerations . . . . . . . . . . . . . . . . . . . . .  25
   9.  Security Considerations . . . . . . . . . . . . . . . . . . .  25
   10. Change history  . . . . . . . . . . . . . . . . . . . . . . .  25
   11. References  . . . . . . . . . . . . . . . . . . . . . . . . .  25
     11.1.  Normative References . . . . . . . . . . . . . . . . . .  25
     11.2.  Informative References . . . . . . . . . . . . . . . . .  26
   Appendix A.  Additional features  . . . . . . . . . . . . . . . .  28
     A.1.  Stream prioritization . . . . . . . . . . . . . . . . . .  28
     A.2.  Computation of autocorrelation function . . . . . . . . .  28
   Authors' Addresses  . . . . . . . . . . . . . . . . . . . . . . .  29

Johansson & Sarker       Expires April 21, 2016                 [Page 2]

Internet-Draft                   SCReAM                     October 2015

1.  Introduction

   Congestion in the Internet is a reality and applications that are
   deployed in the Internet must have congestion control schemes in
   place not only for the robustness of the service that it provides but
   also to ensure the function of the currently deployed Internet.  As
   the interactive realtime communication imposes a great deal of
   requirements on the transport, a robust, efficient rate adaptation
   for all access types is considered as an important part of
   interactive realtime communications as the transmission channel
   bandwidth may vary over time.  Wireless access such as LTE, which is
   an integral part of the current Internet, increases the importance of
   rate adaptation as the channel bandwidth of a default LTE bearer
   [QoS-3GPP] can change considerably in a very short time frame.  Thus
   a rate adaptation solution for interactive realtime media, such as
   WebRTC, must be both quick and be able to operate over a large span
   in available channel bandwidth.  This memo describes a solution,named
   SCReAM, that is based on the self-clocking principle of TCP and uses
   techniques similar to what is used in a new delay based rate
   adaptation algorithm, LEDBAT [RFC6817].

1.1.  Wireless (LTE) access properties

   [I-D.ietf-rmcat-wireless-tests] describes the complications that can
   be observed in wireless environments.  Wireless access such as LTE
   can typically not guarantee a given bandwidth, this is true
   especially for default bearers.  The network throughput may vary
   considerably for instance in cases where the wireless terminal is
   moving around.

   Unlike wireline bottlenecks with large statistical multiplexing it is
   not possible to try to maintain a given bitrate when congestion is
   detected with the hope that other flows will yield, this is because
   there are generally few other flows competing for the same
   bottleneck.  Each user gets its own variable throughput bottleneck,
   where the throughput depends on factors like channel quality, network
   load and historical throughput.  The bottom line is, if the
   throughput drops, the sender has no other option than to reduce the
   bitrate.  In addition, the grace time, i.e. allowed reaction time
   from the time that the congestion is detected until a reaction in
   terms of a rate reduction is effected, is generally very short, in
   the order of one RTT (Round Trip Time).

1.2.  Why is it a self-clocked algorithm?

   Self-clocked congestion control algorithm provides with a benefit
   over the rate based counterparts in that the former consists of two
   parts; the congestion window computation that evolves over a longer

Johansson & Sarker       Expires April 21, 2016                 [Page 3]

Internet-Draft                   SCReAM                     October 2015

   timescale (several RTTs) especially when the congestion window
   evolution is dictated by estimated delay and; the fine grained
   congestion control given by the self-clocking which operates on a
   shorter time scale (1 RTT).
   A rate based congestion control has only one mechanism to adjust the
   sending rate and that makes it more problematic to reach the goal of
   prompt reaction to congestion and also high throughput when channel
   conditions are good.

2.  Terminology

   The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT",
   document are to be interpreted as described in RFC2119 [RFC2119]

3.  Overview of SCReAM Algorithm

   The core SCReAM algorithm has similarities to the concepts of self-
   clocking used in TFWC [TFWC] and follows the packet conservation
   principle.  The packet conservation principle is described as an
   important key-factor behind the protection of networks from
   congestion [PACKET_CONSERVATION].

   In case of SCReAM, the receiver of the media sends the highest
   received sequence number back to the sender, the sender keeps a list
   of transmitted packets and their respective sizes.  This information
   is then used to determine the amount of bytes can be transmitted at
   any given time instant.  A congestion window puts an upper limit on
   how many bytes can be in flight, i.e. transmitted but not yet
   acknowledged.  This is how the packet conservation principle is
   realized.  The congestion window is determined in a way similar to
   LEDBAT [RFC6817].

   LEDBAT is a congestion control algorithm that uses send and receive
   timestamps to estimate the queuing delay along the transmission path.
   The use of LEDBAT ensures that the e2e latency is kept low.  The
   basic functionality is quite simple, there are however a few steps to
   take to make the concept work with conversational media.  In a few
   words they are:

   o  Congestion window validation techniques.  These are similar in
      action as the method described in [I-D.ietf-tcpm-newcwv].  The
      allowed idle period in this draft is shorter than in the
      reference, this to avoid excessive delays in the cases where e.g.
      wireless throughput has decreased during a period where the output
      bitrate has been low.  Furthermore, this draft allows for more
      relaxed rules when the congestion window is allowed to grow, this

Johansson & Sarker       Expires April 21, 2016                 [Page 4]

Internet-Draft                   SCReAM                     October 2015

      is necessary as the variable output bitrate generally means that
      the congestion window is often under-utilized.

   o  Fast increase for quicker bitrate increase.  It makes the media
      bitrate ramp-up within 5 to 10 seconds.  The behavior is similar
      to TCP slowstart.  The fast increase is exited when congestion is
      detected.  The fast increase state can be however be resumed if
      the congestion level is low, this to enable a reasonably quick
      rate increase in case link throughput increases.

   o  A delay trend is computed for earlier detection of incipient
      congestion and as a result it reduces jitter.

   o  Addition of media a rate control function.

   o  Use of inflection points to calculate congestion window and media
      rate to achieve reduced jitter.

   o  Adjustment of delay target for better performance when competing
      with other loss based congestion controlled flows

   The above mentioned features will be described in more detail in
   sections Section 3.1 to Section 3.3.

Johansson & Sarker       Expires April 21, 2016                 [Page 5]

Internet-Draft                   SCReAM                     October 2015

                    |        Media encoder      |
                        ^                  |
                     (3)|               (1)|
                        |                 RTP
                        |                  V
                        |            +-----------+
                   +---------+       |           |
                   | Media   |  (2)  |   Queue   |
                   | rate    |<------|           |
                   | control |       |RTP packets|
                   +---------+       |           |
              +------------+       +--------------+
              |  Network   |  (7)  |    Sender    |
          +-->| congestion |------>| Transmission |
          |   |  control   |       |   Control    |
          |   +------------+       +--------------+
          |                                |
          |   (6)                          |(5)
          |-------------RTCP----------|   RTP
                                      |    |
                                      |    v
                                  |     UDP    |
                                  |   socket   |

                  Figure 1: SCReAM sender functional view

   The SCReAM algorithm constitutes mainly of three parts: network
   congestion control, sender transmission control and media rate
   adaptation.  All these three parts reside at the sender side.
   Figure 1 shows the functional overview of a SCReAM sender.  The
   receiver side algorithm is very simple in comparison as it only
   generates feedback containing acknowledgements to received RTP
   packets, loss count and ECN [RFC6679] count.

Johansson & Sarker       Expires April 21, 2016                 [Page 6]

Internet-Draft                   SCReAM                     October 2015

3.1.  Network Congestion Control

   The congestion control sets an upper limit on how much data can be in
   the network (bytes in flight); this limit is called CWND (congestion
   window) and is used in the sender transmission control.

   The SCReAM congestion control method, uses LEDBAT [RFC6817] to
   measure the one-way delay (OWD).  The OWD can be expressed as the
   estimated queuing delay.  Similar to LEDBAT, it is not necessary to
   use synchronized clocks in sender and receiver in order to compute
   the one way delay.  It is however necessary that they use the same
   clock frequency, or that the clock frequency at the receiver can be
   inferred reliably by the sender.  The SCReAM sender calculates the
   congestion window based on the feedback from the SCReAM receiver.
   The congestion window is allowed to increase if the OWD is below a
   predefined target, otherwise the congestion window decreases.  The
   delay target is typically set to 50-100ms.  This ensures that the OWD
   is kept low on the average.  The reaction to loss events leads to an
   instant reduction of CWND.  Note that the source rate limited nature
   of real time media such as video, typically means that the queuing
   delay will mostly be below the given delay target, this is contrary
   to the case where large files are transmitted using LEDBAT congestion
   control, in which case the queuing delay will stay close to the delay

3.2.  Sender Transmission Control

   Sender Transmission Control limits the output of data, given by the
   relation between the number of bytes in flight and the congestion
   window.  Packet pacing is used to mitigate issues with ACK
   compression that may cause increased jitter and/or packet loss in the
   media traffic.

3.3.  Media Rate Control

   The media rate control serves to adjust the media bitrate to ramp up
   quickly enough to get a fair share of the system resources when link
   throughput increases.

   The reaction to reduced throughput must be prompt in order to avoid
   getting too much data queued up in the RTP packet queues at the
   sender.  The media bitrate is decreased if the RTP queue size exceeds
   a threshold.

   In cases where the sender frame queues increase rapidly such as the
   case of a RAT (Radio Access Type) handover it may be necessary to
   implement additional actions, such as discarding of encoded media
   frames or frame skipping in order to ensure that the RTP queues are

Johansson & Sarker       Expires April 21, 2016                 [Page 7]

Internet-Draft                   SCReAM                     October 2015

   drained quickly.  Frame skipping means that the frame rate is
   temporarily reduced.  Which method to use is a design consideration
   and outside the scope of this algorithm description.

4.  Detailed Description of SCReAM

4.1.  SCReAM Sender

   This section describes the sender side algorithm in more detail.  It
   is a split between the network congestion control and the media rate

   A SCReAM sender implements media rate control and a queue for each
   media type or source, where RTP packets containing encoded media
   frames are temporarily stored for transmission.  Figure 1 shows the
   details when single media sources (a.k.a streams) are used.  However,
   multiple media sources are also supported in the design, in that case
   the sender transmission control will include a transmission
   scheduler.  The transmission scheduler can then enforce the
   priorities for the different streams and act like a coupled
   congestion controller for multiple flows.

   Media frames are encoded and forwarded to the RTP queue (1).  The
   media rate adaptation adapts to the size of the RTP queue (2) and
   controls the media bitrate (3).  The RTP packets are picked from the
   RTP queue (for multiple flows from each queue based on some defined
   priority order or simply in a round robin fashion) (4) by the sender
   transmission controller.  The sender transmission controller (in case
   of multiple flows a transmission scheduler) takes care of the
   transmission of RTP packets, to be written to the UDP socket (5).  In
   the general case all media must go through the sender transmission
   controller and is allowed to be transmitted if the number of bytes in
   flight is less than the congestion window.  RTCP packets are received
   (6) and the information about bytes in flight and congestion window
   is exchanged between the network congestion control and the sender
   transmission control (7).

4.1.1.  Constants and Parameter values

   Constants and state variables are listed in this section.  Constants

   The recommended values for the constants are deduced from
   experimental results.

   OWD_TARGET_LO (0.1s)
     Target value for the minimum OWD

Johansson & Sarker       Expires April 21, 2016                 [Page 8]

Internet-Draft                   SCReAM                     October 2015

   OWD_TARGET_HI (0.4s)
     Target value for the maximum OWD

   OWD_WEIGHT (0.1)
     Averaging factor for owd_fraction_avg

     Headroom for the limitation of CWND

   GAIN (1.0)
     Gain factor for congestion window adjustment

   BETA_LOSS (0.6)
     CWND scale factor due to loss event

   BETA_ECN (0.8)
     CWND scale factor due to ECN event

   BETA_R (0.9)
     Target rate scale factor due to loss event

   MSS (1000 byte)
     Maximum segment size = Max RTP packet size

     Additional slack to the congestion window

     Interval between media bitrate adjustments

     Min target bitrate [bps]

     Max target bitrate [bps]

   RAMP_UP_SPEED (200kbps/s)
     Maximum allowed rate increase speed

     Guard factor against early congestion onset.  A higher value gives
     less jitter, possibly at the expense of a lower link utilization.

   TX_QUEUE_SIZE_FACTOR (0.0..0.2)
     Guard factor against RTP queue buildup

   OWD_TREND_LO (0.2)  Threshold value for owd_trend

Johansson & Sarker       Expires April 21, 2016                 [Page 9]

Internet-Draft                   SCReAM                     October 2015

   T_RESUME_FAST_INCREASE  Time span until fast increase can be resumed,
     given that the owd_trend is below OWD_TREND_LO  State variables

   owd_target (OWD_TARGET_LO)
     OWD target

   owd_fraction_avg (0.0)
     EWMA filtered owd_fraction

   owd_fraction_hist[20] ({0,..,0})
     Vector of the last 20 owd_fraction

   owd_trend (0.0)
     OWD trend, indicates incipient congestion

   owd_trend_mem (0.0)
     Low pass filtered version of owd_trend

   owd_norm_hist[100] ({0,..,0})
     Vector of the last 100 owd_norm

   min_cwnd (2*MSS)
     Minimum congestion window

   in_fast_increase (true)
     True if in fast increase state

   cwnd (min_cwnd)
     Congestion window

   cwnd_last_max (1 byte)
     Congestion window inflection point, i.e. the last known highest
     cwnd.  Used to limit cwnd increase close to the last known
     congestion point.

   bytes_newly_acked (0)
     The number of bytes that was acknowledged with the last received
     acknowledgement i.e. bytes acknowledged since the last CWND update.
     Reset after a CWND update

   send_wnd (0)
     Upper limit of how many bytes that can be transmitted.  Updated
     when CWND is updated and when RTP packet is transmitted

   target_bitrate (0 bps)
     Media target bitrate

Johansson & Sarker       Expires April 21, 2016                [Page 10]

Internet-Draft                   SCReAM                     October 2015

   target_bitrate_last_max (1 bps)
     Media target bitrate inflection point i.e. the last known highest
     target_bitrate.  Used to limit bitrate increase close to the last
     known congestion point

   rate_transmit (0.0 bps)
     Measured transmit bitrate

   rate_ack (0.0 bps)
     Measured throughput based on received acknowledgements

   rate_rtp (0.0 bps)
     Measured bitrate from the media encoder

   rate_rtp_median (0.0 bps)
     Median value of rate_rtp, computed over more than 10s

   s_rtt (0.0s)
     Smoothed RTT [s], computed similar to method depicted in [RFC6298]

   rtp_queue_size (0 bits)
     Size of RTP packets in queue

   rtp_size (0 byte)
     Size of the last transmitted RTP packet

4.1.2.  Network congestion control

   This section explains the network congestion control, it contains two
   main functions

   o  Computation of congestion window at the sender: Gives an upper
      limit to the number of bytes in flight i.e. how many bytes that
      have been transmitted but not yet acknowledged.

   o  Calculation of send window at the sender: RTP packets are
      transmitted if allowed by the relation between the number of bytes
      in flight and the congestion window.  This is controlled by the
      send window.

   Unlike TCP, SCReAM is not a byte oriented protocol, rather it is an
   RTP packet oriented protocol.  Thus a list of transmitted RTP packets
   and their respective transmission times (wall-clock time) is kept for
   further calculation.

   The feedback from the receiver is assumed to consist of the following

Johansson & Sarker       Expires April 21, 2016                [Page 11]

Internet-Draft                   SCReAM                     October 2015

   o  The highest received RTP sequence number.

   o  The wall clock timestamp corresponding to the received RTP packet
      with he highest sequence number.

   o  Accumulated number of lost RTP packets (n_loss).

   o  Accumulated number of ECN-CE marked packets (n_ECN).

   When the sender receives RTCP feedback, the OWD is calculated as
   outlined in [RFC6817] and a number of variables are updated as
   illustrated by the pseudo code below.

       owd_fraction = owd/owd_target
       #calculate moving average
       owd_fraction_avg = (1-OWD_WEIGHT)*owd_fraction_avg+
       # R is an autocorrelation function of owd_fraction_hist
       #  at lag K
       a = R(owd_fraction_hist,1)/R(owd_fraction_hist,0)
       #calculate OWD trend
       owd_trend = a*owd_fraction_avg
       owd_trend_mem = max(0.99*owd_trend_mem, owd_trend)

   The OWD fraction is sampled every 50ms and the last 20 samples are
   stored in a vector (owd_fraction_hist).  This vector is used in the
   computation of an OWD trend that gives a value between 0.0 and 1.0
   depending on the estimated congestion level.  The prediction
   coefficient 'a' has positive values if OWD shows an increasing trend,
   thus an indication of congestion is obtained before the OWD target is
   reached.  The prediction coefficient is further multiplied with
   owd_fraction_avg to reduce sensitivity to increasing OWD when OWD is
   very small.  The owd_trend is utilized in the media rate control to
   indicate incipient congestion and to determine when to exit from fast
   increase mode. owd_trend_mem is used to enforce a less aggressive
   rate increase after congestion events.  The function
   update_owd_fraction_hist(..) removes the oldest element and adds the
   latest owd_fraction element to the owd_fraction_hist vector.

   A loss event is detected if the n_loss counter in the feedback has
   increased since the previous received feedback.  Once a loss event is
   detected, the n_loss counter is ignored for a full smoothed round
   trip time, the intention of this is to limit the congestion window
   decrease to at most once per round trip.
   The congestion window backoff due to loss events is deliberately a
   bit less than is the case with e.g TCP NewReno.  The reason is that

Johansson & Sarker       Expires April 21, 2016                [Page 12]

Internet-Draft                   SCReAM                     October 2015

   TCP is generally used to transmit whole files, which can be
   translated to an infinite source bitrate.  SCReAM on the other hand
   has a source which rate is limited to a value close to the available
   transmit rate and often below said value, the effect of this is that
   SCReAM has less opportunity to grab free capacity than a TCP based
   file transfer.  To compensate for this it is necessary to let SCReAM
   reduce the congestion window slightly less when loss events occur.

   An ECN event is detected if the n_ECN counter in the feedback report
   has increased since the previous received feedback.  Once an ECN
   event is detected, the n_ECN counter is ignored for a full smoothed
   round trip time, the intention of this is to limit the congestion
   window decrease to at most once per round trip.  The congestion
   window backoff due to an ECN event is deliberately smaller than if a
   loss event occurs.  This is inline with the idea outlined in
   [Khademi_alternative_backoff_ECN] to enable ECN marking thresholds
   lower than the corresponding packet drop thresholds.

   The update of congestion window depends on whether a loss or ECN or
   neither occurs.  The pseudo code below describes actions taken in
   case of different events.

     on loss(owd):
       in_fast_increase = false
       cwnd_last_max = cwnd
       cwnd = max(min_cwnd,cwnd*BETA_LOSS)
       adjust_owd_target(owd)#compensating for competing flows

     on ECN(owd):
       in_fast_increase = false
       cwnd_last_max = cwnd
       cwnd = max(min_cwnd,cwnd*BETA_ECN)
       adjust_owd_target(owd)#compensating for competing flows
       calculate_send_window(owd, owd_target)

     # when no loss or ECN event is detected
     on acknowledgement(owd):
       adjust_owd_target(owd) #compensating for competing flows
       calculate_send_window(owd, owd_target)

   The methods are further described in detail below.

Johansson & Sarker       Expires April 21, 2016                [Page 13]

Internet-Draft                   SCReAM                     October 2015  Updating bytes_newly_acked

   The bytes_newly_acked is incremented with a value corresponding to
   how much the highest sequence number has increased since the last
   feedback.  As an example: If the previous acknowledgement indicated
   the highest sequence number N and the new acknowledgement indicated
   N+3, then bytes_newly_acked is incremented by a value equal to the
   sum of the sizes of RTP packets with sequence number N+1, N+2 and
   N+3.  Packets that are lost are also included, which means that even
   though e.g packet N+2 was lost, its size is still included in the
   update of bytes_newly_acked.  Updating congestion window

   The congestion window update is based on OWD, except for the
   occurrence of loss or ECN events, which was described earlier.  OWD
   is obtained from the send and received timestamp of the RTP packets.
   LEDBAT [RFC6817] explains the details of the computation of the OWD.
   An OWD sample is obtained for each received acknowledgement.  No
   smoothing of the OWD samples occur, however some smoothing occurs
   anyway as the computation of the CWND is in itself a low pass filter

   Pseudo code for the update of the congestion window is found below.

Johansson & Sarker       Expires April 21, 2016                [Page 14]

Internet-Draft                   SCReAM                     October 2015

     # additional scaling factor to slow down closer to target
     # The min scale factor is 0.2 to avoid that the congestion window
     #  growth is stalled
     scale = max(0.2,min(1.0,(abs(cwnd-cwnd_last_max)/cwnd_i*4)^2))

     # action depends on whether algorithm is in fast increase
     if (in_fast_increase)
       if(owd_trend >= 0.2)
         cwnd = cwnd + bytes_newly_acked*scale

     # not in fast increase phase
     # off_target calculated as with LEDBAT
     off_target = (owd_target - owd) / owd_target

     gain = GAIN
     # adapt only increase based on scale
     if (off_target > 0)
       gain *= (1 - owd_trend/ 0.2) * scale

     # increase/decrease the congestion window
     # off_target can be positive or negative
     cwnd += gain * off_target * bytes_newly_acked * MSS / cwnd
     # Limit cwnd to the maximum number of bytes in flight
     cwnd = min(cwnd, max_bytes_in_flight*MAX_BYTES_IN_FLIGHT_HEAD_ROOM)
     cwnd = max(cwnd, MIN_CWND)

   CWND is updated differently depending on whether the congestion
   control is in fast increase or not.  A Boolean variable
   in_fast_increase indicates if the congestion is in fast increase

   In fast increase state the congestion window is increased with the
   number of newly acknowledged bytes scaled by a scale factor that
   depends on the relation between CWND and the last known maximum value
   of CWND (cwnd_last_max).  The congestion window growth when
   in_fast_increase is false is dictated by the relation between owd and
   owd_target, also here the scale factor scale factor is applied to
   limit the congestion window growth when cwnd gets close to

Johansson & Sarker       Expires April 21, 2016                [Page 15]

Internet-Draft                   SCReAM                     October 2015

   The scale factor as applied above makes the congestion window grow in
   a similar way as is the case with the Cubic congestion control

   SCReAM calculates the GAIN in a similar way to what is specified in
   [RFC6817].  There are however a few differences.

   o  [RFC6817] specifies a constant GAIN, this specification however
      limits the gain when CWND is increased dependent on near
      congestion state and the relation to the last known max CWND

   o  [RFC6817] specifies that the CWND increased is limited by an
      additional function controlled by a constant ALLOWED_INCREASE.
      This additional limitation is removed in this specification.

   Further the CWND is limited by max_bytes_in_flight and min_cwnd.  The
   limitation of the congestion window by the maximum number of bytes in
   flight over the last 5 seconds (max_bytes_in_flight) avoids possible
   over-estimation of the throughput after for example, idle periods.
   An additional MAX_BYTES_IN_FLIGHT_HEAD_ROOM allows for a slack, to
   allow for a certain amount of media coder output rate variability.

   SCReAM uses the terminology "Bytes in flight (bytes_in_flight)" which
   is computed as the sum of the sizes of the RTP packets ranging from
   the RTP packet most recently transmitted down to but not including
   the acknowledged packet with the highest sequence number.  This can
   be translated to the difference between the highest transmitted byte
   sequence number and the highest acknowledged byte sequence number.
   As an example: If RTP packet with sequence number SN is transmitted
   and the last acknowledgement indicates SN-5 as the highest received
   sequence number then bytes in flight is computed as the sum of the
   size of RTP packets with sequence number SN-4, SN-3, SN-2, SN-1 and
   SN, it does not matter if for instance packet with sequence number
   SN-3 was lost, the size of RTP packet with sequence number SN-3 will
   still be considered in the computation of bytes_in_flight.  Compensation for competing flows

   It is likely that a flow using SCReAM algorithm will have to share
   congested bottlenecks with other flows that use a more aggressive
   congestion control algorithm.  SCReAM takes care of such situations
   by adjusting the owr_target.

Johansson & Sarker       Expires April 21, 2016                [Page 16]

Internet-Draft                   SCReAM                     October 2015

       owd_norm = owd / OWD_TARGET_LOW
       # Compute variance
       owd_norm_var = VARIATION(owd_norm_history(100))
       # Compensation for competing traffic
       if (owd_norm_var < 0.16)
         # Compute average
         owd_norm_avg = AVERAGE(owd_norm_history(20))
         # Update target OWD
         owd_target = owd_norm_avg*OWD_TARGET_LO*1.1
         owd_target = min(OWD_TARGET_HI, owd_target)
         owd_target = max(OWD_TARGET_LO, owd_target)

   The owd_target is adjusted according to the owd_norm_mean_sh whenever
   owd_norm_var is below a given value.  The condition to update
   owd_target is fulfilled if owd_norm_var < 0.16 (indicating that the
   standard deviation is less than 0.4).

   owd_norm is the OWD divided by OWD_TARGET_LO. owd_norm_mean_sh is the
   short term (last 20 samples) average of owd_norm.  owd_norm_var is
   the variance of owd_norm over the last 100 samples.  Send window calculation

   The basic design principle behind packet transmission in SCReAM is to
   allow transmission only if the number of bytes in flight is less than
   the congestion window.  There are however two reasons why this strict
   rule will not work optimally:

   o  Bitrate variations: The media frame size is always varying to a
      larger or smaller extent.  A strict rule as the one given above
      will have the effect that the media bitrate will have difficulties
      to increase as the congestion window puts a too hard restriction
      on the media frame size variation.  This can lead to occasional
      queuing of RTP packets in the RTP packet queue that will further
      prevent bitrate increase.

   o  Reverse (feedback) path congestion: Especially in transport over
      buffer-bloated networks, the one way delay in the reverse
      direction may jump due to congestion.  The effect of this is that
      the acknowledgements are delayed with the result that the self-
      clocking is temporarily halted, even though the forward path is
      not congested.

   The congestion window is adjusted depending on OWD and its relation
   to the OWD target.  When OWD is greater than OWD target the
   congestion window enforces a strict rule that helps to prevent

Johansson & Sarker       Expires April 21, 2016                [Page 17]

Internet-Draft                   SCReAM                     October 2015

   further queue buildup.  When OWD is less than or equal to OWD target
   then an additional slack is added to the congestion window that
   reduces as congestion increases, BYTES_IN_FLIGHT_SLACK is a maximum
   allowed slack in percent.  A large value increases the robustness to
   bitrate variations in the source and congested feedback channel
   issues.  The possible drawback is increased delay or packet loss when
   forward path congestion occurs.  The adjusted congestion window
   (cwnd_s) is used in the send window calculation.

   The send window is given by the relation between the adjusted
   congestion window and the amount of bytes in flight according to the
   pseudo code below.

     calculate_send_window(owd, owd_target)
        # compensate for backward congestion and bitrate variations
        if (owd <= owd_target)
          cwnd_s = max(cwnd*x_cwnd, cwnd+MSS)

        send_wnd = cwnd_s-bytes_in_flight  Resuming fast increase

   Fast increase can be resumed in order to speed up the bitrate
   increase in case congestion abates.  The condition to resume fast
   increase (in_fast_increase = true) is that owd_trend is less than
   OWD_TREND_LO for T_RESUME_FAST_INCREASE seconds or more.

4.1.3.  Media rate control

   The media rate control algorithm is executed at regular intervals
   RATE_ADJUSTMENT_INTERVAL, with the exception of a prompt reaction to
   loss events.  The media rate control operates based on the size of
   the RTP packet send queue and observed loss events.  In addition,
   owd_trend is also considered in the media rate control, this to
   reduce the amount of induced network jitter.

   The role of the media rate control is to strike a reasonable balance
   between a low amount of queuing in the RTP queue and a sufficient
   amount of data to send in order to keep the data path busy.  A too
   cautious setting leads to possible under-utilization of network
   capacity and that the flow is starved out by other, more
   opportunistic traffic, on the other hand a too aggressive setting
   leads to extra jitter.

   A variable target_bitrate is adjusted depending on the congestion
   state.  The target bitrate can vary between a minimum value
   (target_bitrate_min) and a maximum value (target_bitrate_max).

Johansson & Sarker       Expires April 21, 2016                [Page 18]

Internet-Draft                   SCReAM                     October 2015

   For the overall bitrate adjustment, two network throughput estimates
   are computed :

   o  rate_transmit: The measured transmit bitrate

   o  rate_ack: The ACKed bitrate, i.e. the volume of ACKed bits per
      time unit.

   Both estimates are updated every 200ms.

   The current throughput, current_rate, is computed as the maximum
   value of rate_transmit and rate_ack.  The rationale behind the use of
   rate_ack in addition to rate_transmit is that rate_transmit is
   affected also by the amount of data that is available to transmit,
   thus a lack of data to transmit can be seen as reduced throughput
   that may itself cause an unnecessary rate reduction.  To overcome
   this shortcoming; rate_ack is used as well.  This gives a more stable
   throughput estimate.

   Note that rate_ack is updated by bytes_newly_acked, which means that
   even lost packets are regarded as acknowledged.

   The rate change behavior depends on whether a loss event has
   occurred, and if the congestion control is in fast increase or not.

Johansson & Sarker       Expires April 21, 2016                [Page 19]

Internet-Draft                   SCReAM                     October 2015

     # The target_bitrate is updated at a regular interval according

     on loss:
        target_bitrate_last_max = target_bitrate
        target_bitrate = max(BETA_R* target_bitrate, TARGET_BITRATE_MIN)

     if (in_fast_increase = true)
        scl_i = (target_bitrate - target_bitrate_last_max)/
                   (1.0-min(1.0, owd_trend/0.2))
        # Value 0.2 as the bitrate should be allowed to increase
        #  at least slowly --> avoid locking the rate to
        #  target_bitrate_last_max
        increment *= max(0.2, min(1.0, (scl_i*4)^2))
        target_bitrate += increment
        target_bitrate *= (1.0- PRE_CONGESTION_GUARD*owd_trend)
        pre_congestion = min(1.0, max(0.0, owd_fraction_avg-0.3)/0.7)
        pre_congestion += owd_trend
             pre_congestion)-TX_QUEUE_SIZE_FACTOR *rtp_queue_size

     rate_rtp_limit = max(br, max(rate_rtp,rtp_rate_median))
     rate_rtp_limit *= (2.0-1.0*owd_trend_mem)
     target_bitrate = min(target_bitrate, rate_rtp_limit)
     target_bitrate = min(TARGET_BITRATE_MAX,

   In case of a loss event the target_bitrate is updated and the rate
   change procedure is exited.  Otherwise the rate change procedure
   continues.  An ECN event does not cause any action, the reason to
   this is that the congestion window is reduced less due to ECN events
   than loss events, the effect is thus that the expected additional RTP
   queuing delay due to ECN events is so small that an additional
   decrease in media rate is not warranted.

   When in fast increase state, the bitrate increase is given by the
   desired ramp-up speed (RAMP_UP_SPEED) and is limited by the relation
   between the current bitrate and the last known max bitrate.
   Furthermore an increased OWD trend limits the bitrate increase.  The
   setting of RAMP_UP_SPEED depends on preferences, a high setting such
   as 1000kbps/s makes it possible to quickly gain high quality media,

Johansson & Sarker       Expires April 21, 2016                [Page 20]

Internet-Draft                   SCReAM                     October 2015

   this is however at the expense of a higher risk of jitter, which can
   manifest itself as e.g. choppy video rendering.

   When in_fast_increase is false, the bitrate increase is given by the
   current bitrate and is also controlled by the estimated RTP queue and
   the OWD trend, thus it is sufficient that an increased congestion
   level is sensed by the network congestion control to limit the

   In the fast increase phase an allowed increment is computed based on
   the congestion level and the relation to target_bitrate_last_max and
   the target_bitrate is reduced further if congestion is detected.

   If in_fast_increase is false then the target_bitrate_last_max is
   updated to the current value of target_bitrate if in_fast_increase
   was true the last time the bitrate was updated.  Additionally, a pre-
   congestion indicator is computed and the rate is adjusted

   In cases where input stimuli to the media encoder is static, for
   instance in "talking head" scenarios, the target bitrate is not
   always fully utilized.  This may cause undesirable oscillations in
   the target bitrate in the cases where the link throughput is limited
   and the media coder input stimuli changes between static and varying.
   To overcome this issue, the target bitrate is capped to be less than
   a given multiplier of a median value of the history of media coder
   output bitrates, rate_rtp_limit.  A multiplier is applied to
   rate_rtp_limit, depending on congestion history.  The target_bitrate
   is then limited by this rate_rtp_limit.

   Finally the target_bitrate is enforced to be within the defined min
   and max values.

   The vary reader may notice the dependency on the OWD in the
   computation of the target bitrate, this manifests itself in the use
   of the owd_trend and owd_fraction_avg.  As these parameters are used
   also in the network congestion control one may suspect that some odd
   interaction between the media rate control and the network congestion
   control, this is in fact the case if the parameter
   PRE_CONGESTION_GUARD is set to a high value.  The use of owd_trend
   and owd_fraction_avg in the media rate control is solely to reduce
   jitter, the dependency can be removed by setting
   PRE_CONGESTION_GUARD=0, the effect is a somewhat faster rate increase
   at the expense of more jitter.

Johansson & Sarker       Expires April 21, 2016                [Page 21]

Internet-Draft                   SCReAM                     October 2015  FEC and packet overhead considerations

   The target bitrate given by SCReAM depicts the bitrate including RTP
   and FEC overhead.  Therefore it is necessary that the media encoder
   takes this overhead into account when the media bitrate is set.
   It is not strictly necessary to make a 100% perfect compensation for
   the overhead as the SCReAM algorithm will inherently compensate
   moderate errors.  Under-compensation for the overhead has the effect
   that the jitter will increase somewhat while overcompensation will
   have the effect that the bottleneck link becomes under-utilized.

4.2.  SCReAM Receiver

   The simple task of the SCReAM receiver is to feedback
   acknowledgements of received packets, total loss count and total ECN
   count to the SCReAM sender.  Upon reception of each RTP packet the
   receiver will simply maintain enough information to send the
   aforementioned values to the SCReAM sender via RTCP transport layer
   feedback message.  The frequency of the feedback message depends on
   the available RTCP bandwidth.  The details of this feedback is given
   in another document.

5.  Discussion

   This section covers a few discussion points

   o  RTCP feedback overhead: SCReAM benefits from a relatively frequent
      feedback.  Experiments have shown that a feedback rate roughly
      equal to the frame rate gives a stable self-clocking and
      robustness against loss of feedback.  With a maximum bitrate of
      1500kbps the RTCP feedback overhead is in the range 10-15kbps with
      reduced size RTCP [RFC5506], including IP and UDP framing, in
      other words the RTCP overhead is quite modest and should not pose
      a problem in the general case.  Other solutions may be required in
      highly asymmetrical link capacity cases.  Worth notice is that
      SCReAM can work with as low feedback rates as once every 200ms,
      this however comes with a higher sensitivity to loss of feedback
      and also a potential reduction in throughput.

   o  AVPF mode: The RTCP feedback is based on AVPF regular mode.  The
      SCReAM feedback is transmitted as reduced size RTCP so save
      overhead, it is however required to transmit full compound RTCP at
      regular intervals, this interval can be controlled by trr-int
      depicted in [RFC4585].

   o  Clock drift: SCReAM can suffer from the same issues with clock
      drift as is the case with LEDBAT [RFC6817].  Section A.2 in said
      RFC however describes ways to mitigate issues with clock drift.

Johansson & Sarker       Expires April 21, 2016                [Page 22]

Internet-Draft                   SCReAM                     October 2015

6.  Implementation status

   [Editor's note: Please remove the whole section before publication,
   as well reference to RFC 6982]

   This section records the status of known implementations of the
   protocol defined by this specification at the time of posting of this
   Internet-Draft, and is based on a proposal described in [RFC6982].
   The description of implementations in this section is intended to
   assist the IETF in its decision processes in progressing drafts to
   RFCs.  Please note that the listing of any individual implementation
   here does not imply endorsement by the IETF.  Furthermore, no effort
   has been spent to verify the information presented here that was
   supplied by IETF contributors.  This is not intended as, and must not
   be construed to be, a catalog of available implementations or their
   features.  Readers are advised to note that other implementations may

   According to [RFC6982], "this will allow reviewers and working groups
   to assign due consideration to documents that have the benefit of
   running code, which may serve as evidence of valuable experimentation
   and feedback that have made the implemented protocols more mature.
   It is up to the individual working groups to use this information as
   they see it".

6.1.  OpenWebRTC

   The SCReAM algorithm has been implemented in the OpenWebRTC project
   [OpenWebRTC], an open source WebRTC implementation from Ericsson
   Research.  This SCReAM implementation is usable with any WebRTC
   endpoint using OpenWebRTC.

   o  Organization : Ericsson Research, Ericsson.

   o  Name : OpenWebRTC gst plug-in.

   o  Implementation link : The GStreamer plug-in code for SCReAM can be
      found at github repository [SCReAM-Implementation] and is waiting
      to be merged with the master branch of OpebWebRTC repository
      However, people are encouraged to have look at it and send
      feedback.  This wiki
      (https://github.com/EricssonResearch/openwebrtc/wiki) contains
      required information for building and using OpenWebRTC.  Note that
      to get all the SCReAM related code and build them, one has to use
      the cerbero fork from DanielLindstrm' s repository
      (https://github.com/DanielLindstrm/cerbero/tree/scream) instead of
      EricssonResearch fork of cerbero.

Johansson & Sarker       Expires April 21, 2016                [Page 23]

Internet-Draft                   SCReAM                     October 2015

   o  Coverage : The code implements [I-D.ietf-rmcat-scream-cc].  The
      current implementation has been tuned and tested to adapt a video
      stream and does not adapt the audio streams.

   o  Implementation experience : The implementation of the algorithm in
      the OpenWebRTC has given great insight into the algorithm itself
      and its interaction with other involved modules such as encoder,
      RTP queue etc.  In fact it proves the usability of a self-clocked
      rate adaptation algorithm in the real WebRTC system.  The
      implementation experience has led to various algorithm
      improvements both in terms of stability and design.  For example,
      improved rate increase behavior and removal of the ACK vector from
      the feedback message.

   o  Contact : irc://chat.freenode.net/openwebrtc

6.2.  A C++ Implementation of SCReAM

   o  Organization : Ericsson Research, Ericsson.

   o  Name : SCReAM.

   o  Implementation link : A C++ implementation of SCreAM is also
      available which is aimed for doing quick
      experiments[SCReAM-Cplusplus_Implementation].  This repository
      also includes a rudimentary implementation of a simulator.  This
      code can be included in other simulators like NS-3.

   o  Coverage : The code implements [I-D.ietf-rmcat-scream-cc]

   o  Contact : ingemar.s.johansson@ericsson.com,

7.  Acknowledgements

   We would like to thank the following persons for their comments,
   questions and support during the work that led to this memo: Markus
   Andersson, Bo Burman, Tomas Frankkila, Frederic Gabin, Laurits Hamm,
   Hans Hannu, Nikolas Hermanns, Stefan Haakansson, Erlendur Karlsson,
   Daniel Lindstroem, Mats Nordberg, Jonathan Samuelsson, Rickard
   Sjoeberg, Robert Swain, Magnus Westerlund, Stefan Aalund.  Many
   additional thanks to Karen and Mirja for patiently reading,
   suggesting improvements and also for asking all the difficult but
   necessary questions.

Johansson & Sarker       Expires April 21, 2016                [Page 24]

Internet-Draft                   SCReAM                     October 2015

8.  IANA Considerations

   A new RFC4585 transport layer feedback message needs to be

9.  Security Considerations

   The feedback can be vulnerable to attacks similar to those that can
   affect TCP.  It is therefore recommended that the RTCP feedback is at
   least integrity protected.

10.  Change history

   A list of changes:

   o  WG-01 to WG-02: Complete restructuring of the document.  Moved
      feedback message to a separate draft.

   o  WG-00 to WG-01 : Changed the Source code section to Implementation
      status section.

   o  -05 to WG-00 : First version of WG doc, moved additional features
      section to Appendix.  Added description of prioritization in
      SCReAM.  Added description of additional cap on target bitrate

   o  -04 to -05 : ACK vector is replaced by a loss counter, PT is
      removed from feedback, references to source code added

   o  -03 to -04 : Extensive changes due to review comments, code
      somewhat modified, frame skipping made optional

   o  -02 to -03 : Added algorithm description with equations, removed
      pseudo code and simulation results

   o  -01 to -02 : Updated GCC simulation results

   o  -00 to -01 : Fixed a few bugs in example code

11.  References

11.1.  Normative References

   [RFC2119]  Bradner, S., "Key words for use in RFCs to Indicate
              Requirement Levels", BCP 14, RFC 2119,
              DOI 10.17487/RFC2119, March 1997,

Johansson & Sarker       Expires April 21, 2016                [Page 25]

Internet-Draft                   SCReAM                     October 2015

   [RFC3550]  Schulzrinne, H., Casner, S., Frederick, R., and V.
              Jacobson, "RTP: A Transport Protocol for Real-Time
              Applications", STD 64, RFC 3550, DOI 10.17487/RFC3550,
              July 2003, <http://www.rfc-editor.org/info/rfc3550>.

   [RFC4585]  Ott, J., Wenger, S., Sato, N., Burmeister, C., and J. Rey,
              "Extended RTP Profile for Real-time Transport Control
              Protocol (RTCP)-Based Feedback (RTP/AVPF)", RFC 4585,
              DOI 10.17487/RFC4585, July 2006,

   [RFC5506]  Johansson, I. and M. Westerlund, "Support for Reduced-Size
              Real-Time Transport Control Protocol (RTCP): Opportunities
              and Consequences", RFC 5506, DOI 10.17487/RFC5506, April
              2009, <http://www.rfc-editor.org/info/rfc5506>.

   [RFC6298]  Paxson, V., Allman, M., Chu, J., and M. Sargent,
              "Computing TCP's Retransmission Timer", RFC 6298,
              DOI 10.17487/RFC6298, June 2011,

   [RFC6817]  Shalunov, S., Hazel, G., Iyengar, J., and M. Kuehlewind,
              "Low Extra Delay Background Transport (LEDBAT)", RFC 6817,
              DOI 10.17487/RFC6817, December 2012,

11.2.  Informative References

              Zanaty, M., Singh, V., Nandakumar, S., and Z. Sarker, "RTP
              Application Interaction with Congestion Control", draft-
              ietf-rmcat-app-interaction-01 (work in progress), October

              Zanaty, M., Singh, V., Nandakumar, S., and Z. Sarker,
              "Congestion Control and Codec interactions in RTP
              Applications", draft-ietf-rmcat-cc-codec-interactions-01
              (work in progress), October 2015.

              Islam, S., Welzl, M., and S. Gjessing, "Coupled congestion
              control for RTP media", draft-ietf-rmcat-coupled-cc-00
              (work in progress), September 2015.

Johansson & Sarker       Expires April 21, 2016                [Page 26]

Internet-Draft                   SCReAM                     October 2015

              Johansson, I. and Z. Sarker, "Self-Clocked Rate Adaptation
              for Multimedia", draft-ietf-rmcat-scream-cc-01 (work in
              progress), July 2015.

              Sarker, Z. and I. Johansson, "Evaluation Test Cases for
              Interactive Real-Time Media over Wireless Networks",
              draft-ietf-rmcat-wireless-tests-00 (work in progress),
              June 2015.

              Fairhurst, G., Sathiaseelan, A., and R. Secchi, "Updating
              TCP to support Rate-Limited Traffic", draft-ietf-tcpm-
              newcwv-13 (work in progress), June 2015.

              "TCP Alternative Backoff with ECN (ABE)",

              "Open WebRTC project.", <http://www.openwebrtc.io/>.

              "Congestion Avoidance and Control", 1988.

              TS 23.203, 3GPP., "Policy and charging control
              architecture", June 2011, <http://www.3gpp.org/ftp/specs/

   [RFC6679]  Westerlund, M., Johansson, I., Perkins, C., O'Hanlon, P.,
              and K. Carlberg, "Explicit Congestion Notification (ECN)
              for RTP over UDP", RFC 6679, DOI 10.17487/RFC6679, August
              2012, <http://www.rfc-editor.org/info/rfc6679>.

   [RFC6982]  Sheffer, Y. and A. Farrel, "Improving Awareness of Running
              Code: The Implementation Status Section", RFC 6982,
              DOI 10.17487/RFC6982, July 2013,

              "C++ Implementation of SCReAM",

Johansson & Sarker       Expires April 21, 2016                [Page 27]

Internet-Draft                   SCReAM                     October 2015

              "SCReAM Implementation",

   [TFWC]     University College London, "Fairer TCP-Friendly Congestion
              Control Protocol for Multimedia Streaming", December 2007,

Appendix A.  Additional features

   This section describes additional features.  They are not required
   for the basic functionality of SCReAM but can improve performance in
   certain scenarios and topologies.

A.1.  Stream prioritization

   The SCReAM algorithm makes a good distinction between network
   congestion control and the media rate control, an RTP queue queues up
   RTP packets pending transmission.  This is easily extended to many
   streams, in which case RTP packets from two or more RTP queues are
   scheduled at the rate permitted by the network congestion control.

   The scheduling can be done by means of a few different scheduling
   regimes.  For example the method applied in
   [I-D.ietf-rmcat-coupled-cc] can be used.  The implementation of
   SCReAM use something that is referred to as credit based scheduling.
   Credit based scheduling is for instance implemented in IEEE 802.17.
   The short description is that credit is accumulated by queues as they
   wait for service and are spent while the queues are being services.

   For instance, if one queue is allowed to transmit 1000bytes, then a
   credit of 1000bytes is allocated to the other unscheduled queues.
   This principle can be extended to weighted scheduling in which case
   the credit allocated to unscheduled queues depends on the weight

A.2.  Computation of autocorrelation function

   The autocorrelation function is computed over a vector of values.

   Let x be a vector constituting N values, the autocorrelation function
   for a given lag=k for the vector x is given by .

Johansson & Sarker       Expires April 21, 2016                [Page 28]

Internet-Draft                   SCReAM                     October 2015

      R(x,k) = SUM x(n)*x(n+k)

                    Figure 2: Autocorrelation function

Authors' Addresses

   Ingemar Johansson
   Ericsson AB
   Laboratoriegraend 11
   Luleaa  977 53

   Phone: +46 730783289
   Email: ingemar.s.johansson@ericsson.com

   Zaheduzzaman Sarker
   Ericsson AB
   Laboratoriegraend 11
   Luleaa  977 53

   Phone: +46 761153743
   Email: zaheduzzaman.sarker@ericsson.com

Johansson & Sarker       Expires April 21, 2016                [Page 29]