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
draft-ietf-rmcat-scream-cc-02
Abstract
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
4.1.1.1. Constants . . . . . . . . . . . . . . . . . . . . 8
4.1.1.2. State variables . . . . . . . . . . . . . . . . . 10
4.1.2. Network congestion control . . . . . . . . . . . . . 11
4.1.2.1. Updating bytes_newly_acked . . . . . . . . . . . 14
4.1.2.2. Updating congestion window . . . . . . . . . . . 14
4.1.2.3. Compensation for competing flows . . . . . . . . 16
4.1.2.4. Send window calculation . . . . . . . . . . . . . 17
4.1.2.5. Resuming fast increase . . . . . . . . . . . . . 18
4.1.3. Media rate control . . . . . . . . . . . . . . . . . 18
4.1.3.1. 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",
"SHOULD", "SHOULD NOT", "RECOMMENDED", "MAY", and "OPTIONAL" in this
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|
+---------+ | |
+-----------+
|
|
(4)|
RTP
|
v
+------------+ +--------------+
| 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
target.
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
adaptation.
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.
4.1.1.1. 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
MAX_BYTES_IN_FLIGHT_HEAD_ROOM (1.1)
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
BYTES_IN_FLIGHT_SLACK (10%)
Additional slack to the congestion window
RATE_ADJUST_INTERVAL (0.2s)
Interval between media bitrate adjustments
TARGET_BITRATE_MIN
Min target bitrate [bps]
TARGET_BITRATE_MAX
Max target bitrate [bps]
RAMP_UP_SPEED (200kbps/s)
Maximum allowed rate increase speed
PRE_CONGESTION_GUARD (0.0..0.2)
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
4.1.1.2. 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
elements.
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.
update_variables(owd):
owd_fraction = owd/owd_target
#calculate moving average
owd_fraction_avg = (1-OWD_WEIGHT)*owd_fraction_avg+
OWD_WEIGHT*owd_fraction
update_owd_fraction_hist(owd_fraction)
# 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
calculate_send_window(owd,owd_target)
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):
update_bytes_newly_acked()
update_cwnd(bytes_newly_acked)
adjust_owd_target(owd) #compensating for competing flows
calculate_send_window(owd, owd_target)
check_to_resume_fast_increase()
The methods are further described in detail below.
Johansson & Sarker Expires April 21, 2016 [Page 13]
Internet-Draft SCReAM October 2015
4.1.2.1. 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.
4.1.2.2. 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
function.
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
update_cwnd(bytes_newly_acked):
# 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)
in_fast_increase=false
cwnd_i=cwnd
else
cwnd = cwnd + bytes_newly_acked*scale
return
# 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
state.
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
cwnd_last_max.
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
algorithm.
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
value.
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.
4.1.2.3. 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
adjust_owd_target(owd)
owd_norm = owd / OWD_TARGET_LOW
update_owd_norm_history(owd_norm)
# 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.
4.1.2.4. 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)
x_cwnd=1.0+BYTES_IN_FLIGHT_SLACK*(1.0-owd_trend/0.5)/100.0
cwnd_s = max(cwnd*x_cwnd, cwnd+MSS)
send_wnd = cwnd_s-bytes_in_flight
4.1.2.5. 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
# to RATE_ADJUST_INTERVAL
on loss:
target_bitrate_last_max = target_bitrate
target_bitrate = max(BETA_R* target_bitrate, TARGET_BITRATE_MIN)
exit
if (in_fast_increase = true)
scl_i = (target_bitrate - target_bitrate_last_max)/
target_bitrate_last_max
increment = RAMP_UP_SPEED*RATE_ADJUST_INTERVAL*
(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)
else
pre_congestion = min(1.0, max(0.0, owd_fraction_avg-0.3)/0.7)
pre_congestion += owd_trend
target_bitrate=current_rate*(1.0-PRE_CONGESTION_GUARD*
pre_congestion)-TX_QUEUE_SIZE_FACTOR *rtp_queue_size
end
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,
max(TARGET_BITRATE_MIN,target_bitrate))
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
bitrate.
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
accordingly.
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
4.1.3.1. 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
exist.
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
(https://github.com/EricssonResearch/openwebrtc/pull/413).
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,
zaheduzzaman.sarker@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
standardized.
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,
<http://www.rfc-editor.org/info/rfc2119>.
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,
<http://www.rfc-editor.org/info/rfc4585>.
[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,
<http://www.rfc-editor.org/info/rfc6298>.
[RFC6817] Shalunov, S., Hazel, G., Iyengar, J., and M. Kuehlewind,
"Low Extra Delay Background Transport (LEDBAT)", RFC 6817,
DOI 10.17487/RFC6817, December 2012,
<http://www.rfc-editor.org/info/rfc6817>.
11.2. Informative References
[I-D.ietf-rmcat-app-interaction]
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
2014.
[I-D.ietf-rmcat-cc-codec-interactions]
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.
[I-D.ietf-rmcat-coupled-cc]
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
[I-D.ietf-rmcat-scream-cc]
Johansson, I. and Z. Sarker, "Self-Clocked Rate Adaptation
for Multimedia", draft-ietf-rmcat-scream-cc-01 (work in
progress), July 2015.
[I-D.ietf-rmcat-wireless-tests]
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.
[I-D.ietf-tcpm-newcwv]
Fairhurst, G., Sathiaseelan, A., and R. Secchi, "Updating
TCP to support Rate-Limited Traffic", draft-ietf-tcpm-
newcwv-13 (work in progress), June 2015.
[Khademi_alternative_backoff_ECN]
"TCP Alternative Backoff with ECN (ABE)",
<https://tools.ietf.org/html/draft-khademi-
alternativebackoff-ecn-00>.
[OpenWebRTC]
"Open WebRTC project.", <http://www.openwebrtc.io/>.
[PACKET_CONSERVATION]
"Congestion Avoidance and Control", 1988.
[QoS-3GPP]
TS 23.203, 3GPP., "Policy and charging control
architecture", June 2011, <http://www.3gpp.org/ftp/specs/
archive/23_series/23.203/23203-990.zip>.
[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,
<http://www.rfc-editor.org/info/rfc6982>.
[SCReAM-Cplusplus_Implementation]
"C++ Implementation of SCReAM",
<https://github.com/EricssonResearch/scream>.
Johansson & Sarker Expires April 21, 2016 [Page 27]
Internet-Draft SCReAM October 2015
[SCReAM-Implementation]
"SCReAM Implementation",
<https://github.com/DanielLindstrm/openwebrtc-gst-
plugins/tree/scream>.
[TFWC] University College London, "Fairer TCP-Friendly Congestion
Control Protocol for Multimedia Streaming", December 2007,
<http://www-dept.cs.ucl.ac.uk/staff/M.Handley/papers/
tfwc-conext.pdf>.
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
allocation.
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
n=N-k
R(x,k) = SUM x(n)*x(n+k)
n=1
Figure 2: Autocorrelation function
Authors' Addresses
Ingemar Johansson
Ericsson AB
Laboratoriegraend 11
Luleaa 977 53
Sweden
Phone: +46 730783289
Email: ingemar.s.johansson@ericsson.com
Zaheduzzaman Sarker
Ericsson AB
Laboratoriegraend 11
Luleaa 977 53
Sweden
Phone: +46 761153743
Email: zaheduzzaman.sarker@ericsson.com
Johansson & Sarker Expires April 21, 2016 [Page 29]
