Документ взят из кэша поисковой машины. Адрес оригинального документа : http://mirror.msu.net/pub/rfc-editor/internet-drafts/draft-ietf-rmcat-nada-02.txt Дата изменения: Fri Mar 18 19:44:20 2016 Дата индексирования: Sun Apr 10 06:33:20 2016 Кодировка: Поисковые слова: horizon

Network Working Group X. Zhu
Internet-Draft R. Pan
Intended status: Experimental M. Ramalho
Expires: September 19, 2016 S. Mena
P. Jones
J. Fu
Cisco Systems
S. D'Aronco
EPFL
C. Ganzhorn
March 18, 2016


NADA: A Unified Congestion Control Scheme for Real-Time Media
draft-ietf-rmcat-nada-02

Abstract

This document describes NADA (network-assisted dynamic adaptation), a
novel congestion control scheme for interactive real-time media
applications, such as video conferencing. In the proposed scheme,
the sender regulates its sending rate based on either implicit or
explicit congestion signaling, in a unified approach. The scheme can
benefit from explicit congestion notification (ECN) markings from
network nodes. It also maintains consistent sender behavior in the
absence of such markings, by reacting to queuing delays and packet
losses instead.

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
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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 September 19, 2016.







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Copyright Notice

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

This document is subject to BCP 78 and the IETF Trust's Legal
Provisions Relating to IETF Documents
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the Trust Legal Provisions and are provided without warranty as
described in the Simplified BSD License.

Table of Contents

1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 3
2. Terminology . . . . . . . . . . . . . . . . . . . . . . . . . 3
3. System Overview . . . . . . . . . . . . . . . . . . . . . . . 3
4. Core Congestion Control Algorithm . . . . . . . . . . . . . . 5
4.1. Mathematical Notations . . . . . . . . . . . . . . . . . 5
4.2. Receiver-Side Algorithm . . . . . . . . . . . . . . . . . 8
4.3. Sender-Side Algorithm . . . . . . . . . . . . . . . . . . 10
5. Practical Implementation of NADA . . . . . . . . . . . . . . 12
5.1. Receiver-Side Operation . . . . . . . . . . . . . . . . . 12
5.1.1. Estimation of one-way delay and queuing delay . . . . 12
5.1.2. Estimation of packet loss/marking ratio . . . . . . . 12
5.1.3. Estimation of receiving rate . . . . . . . . . . . . 13
5.2. Sender-Side Operation . . . . . . . . . . . . . . . . . . 13
5.2.1. Rate shaping buffer . . . . . . . . . . . . . . . . . 14
5.2.2. Adjusting video target rate and sending rate . . . . 15
5.3. Feedback Message Requirements . . . . . . . . . . . . . . 15
6. Discussions and Further Investigations . . . . . . . . . . . 16
6.1. Choice of delay metrics . . . . . . . . . . . . . . . . . 16
6.2. Method for delay, loss, and marking ratio estimation . . 16
6.3. Impact of parameter values . . . . . . . . . . . . . . . 17
6.4. Sender-based vs. receiver-based calculation . . . . . . . 18
6.5. Incremental deployment . . . . . . . . . . . . . . . . . 18
7. Implementation Status . . . . . . . . . . . . . . . . . . . . 18
8. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 19
9. Acknowledgements . . . . . . . . . . . . . . . . . . . . . . 19
10. References . . . . . . . . . . . . . . . . . . . . . . . . . 19
10.1. Normative References . . . . . . . . . . . . . . . . . . 19
10.2. Informative References . . . . . . . . . . . . . . . . . 20
Appendix A. Network Node Operations . . . . . . . . . . . . . . 21
A.1. Default behavior of drop tail queues . . . . . . . . . . 22
A.2. RED-based ECN marking . . . . . . . . . . . . . . . . . . 22



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A.3. Random Early Marking with Virtual Queues . . . . . . . . 22
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 23

1. Introduction

Interactive real-time media applications introduce a unique set of
challenges for congestion control. Unlike TCP, the mechanism used
for real-time media needs to adapt quickly to instantaneous bandwidth
changes, accommodate fluctuations in the output of video encoder rate
control, and cause low queuing delay over the network. An ideal
scheme should also make effective use of all types of congestion
signals, including packet loss, queuing delay, and explicit
congestion notification (ECN) [RFC3168] markings. The requirements
for the congestion control algorithm are outlined in
[I-D.ietf-rmcat-cc-requirements].

This document describes an experimental congestion control scheme
called network-assisted dynamic adaptation (NADA). The NADA design
benefits from explicit congestion control signals (e.g., ECN
markings) from the network, yet also operates when only implicit
congestion indicators (delay and/or loss) are available. Such a
unified sender behavior distinguishes NADA from other congestion
control schemes for real-time media. In addition, its core
congestion control algorithm is designed to guarantee stability for
path round-trip-times (RTTs) below a prescribed bound (e.g., 250ms
with default parameter choices). It further supports weighted
bandwidth sharing among competing video flows with different
priorities. The signaling mechanism consists of standard RTP
timestamp [RFC3550] and RTCP feedback reports with non-standard
messages.

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 [RFC2119].

3. System Overview

Figure 1 shows the end-to-end system for real-time media transport
that NADA operates in. Note that there also exist network nodes
along the reverse (potentially uncongested) path that the RTCP
feedback reports traverse. Those network nodes are not shown in the
figure for sake of abrevity.







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+---------+ r_vin +--------+ +--------+ +----------+
| Media |<--------| RTP | |Network | | RTP |
| Encoder |========>| Sender |=======>| Node |====>| Receiver |
+---------+ r_vout +--------+ r_send +--------+ +----------+
/|\ |
| |
+---------------------------------+
RTCP Feedback Report

Figure 1: System Overview

o Media encoder with rate control capabilities. It encodes raw
media (audio and video) frames into compressed bitstream which is
later packetized into RTP packets. As discussed in
[I-D.ietf-rmcat-video-traffic-model], the actual output rate from
the encoder r_vout may fluctuate around the target r_vin.
Furthermore, it is possible that the encoder can only react to bit
rate changes at rather coarse time intervals, e.g., once every 0.5
seconds.

o RTP sender: responsible for calculating the NADA reference rate
based on network congestion indicators (delay, loss, or ECN
marking reports from the receiver), for updating the video encoder
with a new target rate r_vin, and for regulating the actual
sending rate r_send accordingly. The RTP sender also generates a
sending timestamp for each outgoing packet.

o RTP receiver: responsible for measuring and estimating end-to-end
delay (based on sender timestamp), packet loss (based on RTP
sequence number), ECN marking ratios (based on [RFC6679]), and
receiving rate (r_recv) of the flow. It calculates the aggregated
congestion signal (x_curr) that accounts for queuing delay, ECN
markings, and packet losses. The receiver also determines the
mode for sender rate adaptation (rmode) based on whether the flow
has encountered any standing non-zero congestion. The receiver
sends periodic RTCP reports back to the sender, containing values
of x_curr, rmode, and r_recv.

o Network node with several modes of operation. The system can work
with the default behavior of a simple drop tail queue. It can
also benefit from advanced AQM features such as PIE, FQ-CoDel,
RED-based ECN marking, and PCN marking using a token bucket
algorithm. Note that network node operation is out of control for
the design of NADA.







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4. Core Congestion Control Algorithm

Like TCP-Friendly Rate Control (TFRC) [Floyd-CCR00] [RFC5348], NADA
is a rate-based congestion control algorithm. In its simplest form,
the sender reacts to the collection of network congestion indicators
in the form of an aggregated congestion signal, and operates in one
of two modes:

o Accelerated ramp-up: when the bottleneck is deemed to be
underutilized, the rate increases multiplicatively with respect to
the rate of previously successful transmissions. The rate
increase mutliplier (gamma) is calculated based on observed round-
trip-time and target feedback interval, so as to limit self-
inflicted queuing delay.

o Gradual rate update: in the presence of non-zero aggregate
congestion signal, the sending rate is adjusted in reaction to
both its value (x_curr) and its change in value (x_diff).

This section introduces the list of mathematical notations and
describes the core congestion control algorithm at the sender and
receiver, respectively. Additional details on recommended practical
implementations are described in Section 5.1 and Section 5.2.

4.1. Mathematical Notations

This section summarizes the list of variables and parameters used in
the NADA algorithm.























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+--------------+-------------------------------------------------+
| Notation | Variable Name |
+--------------+-------------------------------------------------+
| t_curr | Current timestamp |
| t_last | Last time sending/receiving a feedback |
| delta | Observed interval between current and previous |
| | feedback reports: delta = t_curr-t_last |
| r_ref | Reference rate based on network congestion |
| r_send | Sending rate |
| r_recv | Receiving rate |
| r_vin | Target rate for video encoder |
| r_vout | Output rate from video encoder |
| d_base | Estimated baseline delay |
| d_fwd | Measured and filtered one-way delay |
| d_queue | Estimated queueing delay |
| d_tilde | Equivalent delay after non-linear warping |
| p_mark | Estimated packet ECN marking ratio |
| p_loss | Estimated packet loss ratio |
| x_curr | Aggregate congestion signal |
| x_prev | Previous value of aggregate congestion signal |
| x_diff | Change in aggregate congestion signal w.r.t. |
| | its previous value: x_diff = x_curr - x_prev |
| rmode | Rate update mode: (0 = accelerated ramp-up; |
| | 1 = gradual update) |
| gamma | Rate increase multiplier in accelerated ramp-up |
| | mode |
| rtt | Estimated round-trip-time at sender |
| buffer_len | Rate shaping buffer occupancy measured in bytes |
+--------------+-------------------------------------------------+

Figure 2: List of variables.




















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+---------------+---------------------------------+----------------+
| Notation | Parameter Name | Default Value |
+--------------+----------------------------------+----------------+
| PRIO | Weight of priority of the flow | 1.0
| RMIN | Minimum rate of application | 150 Kbps |
| | supported by media encoder | |
| RMAX | Maximum rate of application | 1.5 Mbps |
| | supported by media encoder | |
| XREF | Reference congestion level | 20ms |
| KAPPA | Scaling parameter for gradual | 0.5 |
| | rate update calculation | |
| ETA | Scaling parameter for gradual | 2.0 |
| | rate update calculation | |
| TAU | Upper bound of RTT in gradual | 500ms |
| | rate update calculation | |
| DELTA | Target feedback interval | 100ms |
| DFILT | Bound on filtering delay | 120ms |
| LOGWIN | Observation window in time for | 500ms |
| | calculating packet summary | |
| | statistics at receiver | |
| QEPS | Threshold for determining queuing| 10ms |
| | delay build up at receiver | |
+..............+..................................+................+
| QTH | Delay threshold for non-linear | 50ms |
| | warping | |
| QMAX | Delay upper bound for non-linear | 400ms |
| | warping | |
| DLOSS | Delay penalty for loss | 1.0s |
| DMARK | Delay penalty for ECN marking | 200ms |
+..............+..................................+................+
| GAMMA_MAX | Upper bound on rate increase | 50% |
| | ratio for accelerated ramp-up | |
| QBOUND | Upper bound on self-inflicted | 50ms |
| | queuing delay during ramp up | |
+..............+..................................+................+
| FPS | Frame rate of incoming video | 30 |
| BETA_S | Scaling parameter for modulating | 0.1 |
| | outgoing sending rate | |
| BETA_V | Scaling parameter for modulating | 0.1 |
| | video encoder target rate | |
| ALPHA | Smoothing factor in exponential | 0.1 |
| | smoothing of packet loss and | |
| | marking ratios |
+--------------+----------------------------------+----------------+

Figure 3: List of algorithm parameters.





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4.2. Receiver-Side Algorithm

The receiver-side algorithm can be outlined as below:

On initialization:
set d_base = +INFINITY
set p_loss = 0
set p_mark = 0
set r_recv = 0
set both t_last and t_curr as current time

On receiving a media packet:
obtain current timestamp t_curr from system clock
obtain from packet header sending time stamp t_sent
obtain one-way delay measurement: d_fwd = t_curr - t_sent
update baseline delay: d_base = min(d_base, d_fwd)
update queuing delay: d_queue = d_fwd - d_base
update packet loss ratio estimate p_loss
update packet marking ratio estimate p_mark
update measurement of receiving rate r_recv

On time to send a new feedback report (t_curr - t_last > DELTA):
calculate non-linear warping of delay d_tilde if packet loss exists
calculate current aggregate congestion signal x_curr
determine mode of rate adaptation for sender: rmode
send RTCP feedback report containing values of: rmode, x_curr, and r_recv
update t_last = t_curr

In order for a delay-based flow to hold its ground when competing
against loss-based flows (e.g., loss-based TCP), it is important to
distinguish between different levels of observed queuing delay. For
instance, a moderate queuing delay value below 100ms is likely self-
inflicted or induced by other delay-based flows, whereas a high
queuing delay value of several hundreds of milliseconds may indicate
the presence of a loss-based flow that does not refrain from
increased delay.

When packet losses are observed, the estimated queuing delay follows
a non-linear warping inspired by the delay-adaptive congestion window
backoff policy in [Budzisz-TON11]:











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/ d_queue, if d_queue |
| (QMAX - d_queue)^4
d_tilde = < QTH ------------------, if QTH | (QMAX - QTH)^4
|
\ 0, otherwise.

Here, the queuing delay value is unchanged when it is below the first
threshold QTH; it is scaled down following a non-linear curve when
its value falls between QTH and QMAX; above QMAX, the high queuing
delay value no longer counts toward congestion control.

The aggregate congestion signal is:


x_curr = d_tilde + p_mark*DMARK + p_loss*DLOSS. (2)


Here, DMARK is prescribed delay penalty associated with ECN markings
and DLOSS is prescribed delay penalty associated with packet losses.
The value of DLOSS and DMARK does not depend on configurations at the
network node. Since ECN-enabled active queue management schemes
typically mark a packet before dropping it, the value of DLOSS SHOULD
be higher than that of DMARK. Furthermore, the values of DLOS and
DMARK need to be set consistently across all NADA flows for them to
compete fairly.

In the absence of packet marking and losses, the value of x_curr
reduces to the observed queuing delay d_queue. In that case the NADA
algorithm operates in the regime of delay-based adaptation.

Given observed per-packet delay and loss information, the receiver is
also in a good position to determine whether the network is
underutilized and recommend the corresponding rate adaptation mode
for the sender. The criteria for operating in accelerated ramp-up
mode are:

o No recent packet losses within the observation window LOGWIN; and

o No build-up of queuing delay: d_fwd-d_base < QEPS for all previous
delay samples within the observation window LOGWIN.

Otherwise the algorithm operates in graduate update mode.







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4.3. Sender-Side Algorithm

The sender-side algorithm is outlined as follows:

on initialization:
set r_ref = RMIN
set rtt = 0
set x_prev = 0
set t_last and t_curr as current system clock time

on receiving feedback report:
obtain current timestamp from system clock: t_curr
obtain values of rmode, x_curr, and r_recv from feedback report
update estimation of rtt
measure feedback interval: delta = t_curr - t_last
if rmode == 0:
update r_ref following accelerated ramp-up rules
else:
update r_ref following gradual update rules
clip rate r_ref within the range of [RMIN, RMAX]
x_prev = x_curr
t_last = t_curr

In accelerated ramp-up mode, the rate r_ref is updated as follows:

QBOUND
gamma = min(GAMMA_MAX, ------------------) (3)
rtt+DELTA+DFILT

r_ref = max(r_ref, (1+gamma) r_recv) (4)


The rate increase multiplier gamma is calculated as a function of
upper bound of self-inflicted queuing delay (QBOUND), round-trip-time
(rtt), target feedback interval (DELTA) and bound on filtering delay
for calculating d_queue (DFILT). It has a maximum value of
GAMMA_MAX. The rationale behind (3)-(4) is that the longer it takes
for the sender to observe self-inflicted queuing delay build-up, the
more conservative the sender should be in increasing its rate, hence
the smaller the rate increase multiplier.

In gradual update mode, the rate r_ref is updated as:









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x_offset = x_curr - PRIO*XREF*RMAX/r_ref (5)

x_diff = x_curr - x_prev (6)

delta x_offset
r_ref = r_ref - KAPPA*-------*------------*r_ref
TAU TAU

x_diff
- KAPPA*ETA*---------*r_ref (7)
TAU

The rate changes in proportion to the previous rate decision. It is
affected by two terms: offset of the aggregate congestion signal from
its value at equilibrium (x_offset) and its change (x_diff).
Calculation of x_offset depends on maximum rate of the flow (RMAX),
its weight of priority (PRIO), as well as a reference congestion
signal (XREF). The value of XREF is chosen so that the maximum rate
of RMAX can be achieved when the observed congestion signal level is
below PRIO*XREF.

At equilibrium, the aggregated congestion signal stablizes at x_curr
= PRIO*XREF*RMAX/r_ref. This ensures that when multiple flows share
the same bottleneck and observe a common value of x_curr, their rates
at equilibrium will be proportional to their respective priority
levels (PRIO) and maximum rate (RMAX). Values of RMIN and RMAX will
be provided by the media codec, as specified in
[I-D.ietf-rmcat-cc-codec-interactions]. In the absense of such
information, NADA sender will choose a default value of 0 for RMIN,
and 2Mbps for RMAX.

As mentioned in the sender-side algorithm, the final rate is clipped
within the dynamic range specified by the application:


r_ref = min(r_ref, RMAX) (8)

r_ref = max(r_ref, RMIN) (9)


The above operations ignore many practical issues such as clock
synchronization between sender and receiver, filtering of noise in
delay measurements, and base delay expiration. These will be
addressed in Section 5







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5. Practical Implementation of NADA

5.1. Receiver-Side Operation

The receiver continuously monitors end-to-end per-packet statistics
in terms of delay, loss, and/or ECN marking ratios. It then
aggregates all forms of congestion indicators into the form of an
equivalent delay and periodically reports this back to the sender.
In addition, the receiver tracks the receiving rate of the flow and
includes that in the feedback message.

5.1.1. Estimation of one-way delay and queuing delay

The delay estimation process in NADA follows a similar approach as in
earlier delay-based congestion control schemes, such as LEDBAT
[RFC6817]. Instead of relying on RTP timestamps, the NADA sender
generates its own timestamp based on local system clock and embeds
that information in the transport packet header. The NADA receiver
estimates the forward delay as having a constant base delay component
plus a time varying queuing delay component. The base delay is
estimated as the minimum value of one-way delay observed over a
relatively long period (e.g., tens of minutes), whereas the
individual queuing delay value is taken to be the difference between
one-way delay and base delay. All delay estimations are based on
sender timestamps with higher granularity than RTP timestamps.

The individual sample values of queuing delay should be further
filtered against various non-congestion-induced noise, such as spikes
due to processing "hiccup" at the network nodes. Current
implementation employs a 15-tap minimum filter over per-packet
queuing delay estimates.

5.1.2. Estimation of packet loss/marking ratio

The receiver detects packet losses via gaps in the RTP sequence
numbers of received packets. Packets arriving out-of-order are
discarded, and count towards losses. The instantaneous packet loss
ratio p_inst is estimated as the ratio between the number of missing
packets over the number of total transmitted packets within the
recent observation window LOGWIN. The packet loss ratio p_loss is
obtained after exponential smoothing:

p_loss = ALPHA*p_inst + (1-ALPHA)*p_loss. (10)

The filtered result is reported back to the sender as the observed
packet loss ratio p_loss.





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Estimation of packet marking ratio p_mark follows the same procedure
as above. It is assumed that ECN marking information at the IP
header can be passed to the receiving endpoint, e.g., by following
the mechanism described in [RFC6679].

5.1.3. Estimation of receiving rate

It is fairly straighforward to estimate the receiving rate r_recv.
NADA maintains a recent observation window with time span of LOGWIN,
and simply divides the total size of packets arriving during that
window over the time span. The receiving rate (r_recv) is included
as part of the feedback report.

5.2. Sender-Side Operation

Figure 4 provides a detailed view of the NADA sender. Upon receipt
of an RTCP feedback report from the receiver, the NADA sender
calculates the reference rate r_ref as specified in Section 4.3. It
further adjusts both the target rate for the live video encoder r_vin
and the sending rate r_send over the network based on the updated
value of r_ref and rate shaping buffer occupancy buffer_len.

The NADA sender behavior stays the same in the presence of all types
of congestion indicators: delay, loss, and ECN marking. This unified
approach allows a graceful transition of the scheme as the network
shifts dynamically between light and heavy congestion levels.

























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+----------------+
| Calculate | <---- RTCP report
| Reference Rate |
-----------------+
| r_ref
+------------+-------------+
| |
\|/ \|/
+-----------------+ +---------------+
| Calculate Video | | Calculate |
| Target Rate | | Sending Rate |
+-----------------+ +---------------+
| /|\ /|\ |
r_vin | | | |
\|/ +-------------------+ |
+----------+ | buffer_len | r_send
| Video | r_vout -----------+ \|/
| Encoder |--------> |||||||||=================>
+----------+ -----------+ RTP packets
Rate Shaping Buffer

Figure 4: NADA Sender Structure

5.2.1. Rate shaping buffer

The operation of the live video encoder is out of the scope of the
design for the congestion control scheme in NADA. Instead, its
behavior is treated as a black box.

A rate shaping buffer is employed to absorb any instantaneous
mismatch between encoder rate output r_vout and regulated sending
rate r_send. Its current level of occupancy is measured in bytes and
is denoted as buffer_len.

A large rate shaping buffer contributes to higher end-to-end delay,
which may harm the performance of real-time media communications.
Therefore, the sender has a strong incentive to prevent the rate
shaping buffer from building up. The mechanisms adopted are:

o To deplete the rate shaping buffer faster by increasing the
sending rate r_send; and

o To limit incoming packets of the rate shaping buffer by reducing
the video encoder target rate r_vin.







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5.2.2. Adjusting video target rate and sending rate

The target rate for the live video encoder deviates from the network
congestion control rate r_ref based on the level of occupancy in the
rate shaping buffer:

r_vin = r_ref - BETA_V*8*buffer_len*FPS. (11)

The actual sending rate r_send is regulated in a similar fashion:

r_send = r_ref + BETA_S*8*buffer_len*FPS. (12)

In (11) and (12), the first term indicates the rate calculated from
network congestion feedback alone. The second term indicates the
influence of the rate shaping buffer. A large rate shaping buffer
nudges the encoder target rate slightly below -- and the sending rate
slightly above -- the reference rate r_ref.

Intuitively, the amount of extra rate offset needed to completely
drain the rate shaping buffer within the duration of a single video
frame is given by 8*buffer_len*FPS, where FPS stands for the frame
rate of the video. The scaling parameters BETA_V and BETA_S can be
tuned to balance between the competing goals of maintaining a small
rate shaping buffer and deviating from the reference rate point.

5.3. Feedback Message Requirements

The following list of information is required for NADA congestion
control to function properly:

o Recommended rate adaptation mode (rmode): a 1-bit flag indicating
whether the sender should operate in accelerated ramp-up mode
(rmode=0) or gradual update mode (rmode=1).

o Aggregated congestion signal (x_curr): the most recently updated
value, calculated by the receiver according to Section 4.2. This
information is expressed with a unit of 100 microsecond (i.e.,
1/10 of a millisecond) in 15 bits. This allows a maximum value of
x_curr at approximately 3.27 second.

o Receiving rate (r_recv): the most recently measured receiving rate
according to Section 5.1.3. This information is expressed with a
unit of 10 Kilobits per second (Kbps) in 16 bits. This allows a
maximum rate of approximately 6.55Mbps.

The above list of information can be accommodated by 32 bits in
total. Choice of the feedback message interval DELTA is discussed in
Section 6.3 A target feedback interval of DELTA=100ms is recommended.



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6. Discussions and Further Investigations

6.1. Choice of delay metrics

The current design works with relative one-way-delay (OWD) as the
main indication of congestion. The value of the relative OWD is
obtained by maintaining the minimum value of observed OWD over a
relatively long time horizon and subtract that out from the observed
absolute OWD value. Such an approach cancels out the fixed
difference between the sender and receiver clocks. It has been
widely adopted by other delay-based congestion control approaches
such as [RFC6817]. As discussed in [RFC6817], the time horizon for
tracking the minimum OWD needs to be chosen with care: it must be
long enough for an opportunity to observe the minimum OWD with zero
standing queue along the path, and sufficiently short so as to timely
reflect "true" changes in minimum OWD introduced by route changes and
other rare events.

The potential drawback in relying on relative OWD as the congestion
signal is that when multiple flows share the same bottleneck, the
flow arriving late at the network experiencing a non-empty queue may
mistakenly consider the standing queuing delay as part of the fixed
path propagation delay. This will lead to slightly unfair bandwidth
sharing among the flows.

Alternatively, one could move the per-packet statistical handling to
the sender instead and use relative round-trip-time (RTT) in lieu of
relative OWD, assuming that per-packet acknowledgements are
available. The main drawback of RTT-based approach is the noise in
the measured delay in the reverse direction.

Note that the choice of either delay metric (relative OWD vs. RTT)
involves no change in the proposed rate adaptation algorithm.
Therefore, comparing the pros and cons regarding which delay metric
to adopt can be kept as an orthogonal direction of investigation.

6.2. Method for delay, loss, and marking ratio estimation

Like other delay-based congestion control schemes, performance of
NADA depends on the accuracy of its delay measurement and estimation
module. Appendix A in [RFC6817] provides an extensive discussion on
this aspect.

The current recommended practice of simply applying a 15-tab minimum
filter suffices in guarding against processing delay outliers
observed in wired connections. For wireless connections with a
higher packet delay variation (PDV), more sophisticated techniques on
de-noising, outlier rejection, and trend analysis may be needed.



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More sophisticated methods in packet loss ratio calculation, such as
that adopted by [Floyd-CCR00], will likely be beneficial. These
alternatives are currently under investigation.

6.3. Impact of parameter values

In the gradual rate update mode, the parameter TAU indicates the
upper bound of round-trip-time (RTT) in feedback control loop.
Typically, the observed feedback interval delta is close to the
target feedback interval DELTA, and the relative ratio of delta/TAU
versus ETA dictates the relative strength of influence from the
aggregate congestion signal offset term (x_offset) versus its recent
change (x_diff), respectively. These two terms are analogous to the
integral and proportional terms in a proportional-integral (PI)
controller. The recommended choice of TAU=500ms, DELTA=100ms and ETA
= 2.0 corresponds to a relative ratio of 1:10 between the gains of
the integral and proportional terms. Consequently, the rate
adaptation is mostly driven by the change in the congestion signal
with a long-term shift towards its equilibrium value driven by the
offset term. Finally, the scaling parameter KAPPA determines the
overall speed of the adaptation and needs to strike a balance between
responsiveness and stability.

The choice of the target feedback interval DELTA needs to strike the
right balance between timely feedback and low RTCP feedback message
counts. A target feedback interval of DELTA=100ms is recommended,
corresponding to a feedback bandwidth of 16Kbps with 200 bytes per
feedback message --- less than 0.1% overhead for a 1 Mbps flow.
Furthermore, both simulation studies and frequency-domain analysis
have established that a feedback interval below 250ms will not break
up the feedback control loop of NADA congestion control.

In calculating the non-linear warping of delay in (1), the current
design uses fixed values of QTH and QMAX. It is possible to adapt
the value of both based on past observations of queuing delay in the
presence of packet losses.

In calculating the aggregate congestion signal x_curr, the choice of
DMARK and DLOSS influence the steady-state packet loss/marking ratio
experienced by the flow at a given available bandwidth. Higher
values of DMARK and DLOSS result in lower steady-state loss/marking
ratios, but are more susceptible to the impact of individual packet
loss/marking events. While the value of DMARK and DLOSS are fixed
and predetermined in the current design, a scheme for automatically
tuning these values based on desired bandwidth sharing behavior in
the presence of other competing loss-based flows (e.g., loss-based
TCP) is under investigation.




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[Editor's note: Choice of start value: is this in scope of congestion
control, or should this be decided by the application?]

6.4. Sender-based vs. receiver-based calculation

In the current design, the aggregated congestion signal x_curr is
calculated at the receiver, keeping the sender operation completely
independent of the form of actual network congestion indications
(delay, loss, or marking). Alternatively, one can move the logics of
(1) and (2) to the sender. Such an approach requires slightly higher
overhead in the feedback messages, which should contain individual
fields on queuing delay (d_queue), packet loss ratio (p_loss), packet
marking ratio (p_mark), receiving rate (r_recv), and recommended rate
adaptation mode (rmode).

6.5. Incremental deployment

One nice property of NADA is the consistent video endpoint behavior
irrespective of network node variations. This facilitates gradual,
incremental adoption of the scheme.

To start off with, the proposed congestion control mechanism can be
implemented without any explicit support from the network, and relies
solely on observed one-way delay measurements and packet loss ratios
as implicit congestion signals.

When ECN is enabled at the network nodes with RED-based marking, the
receiver can fold its observations of ECN markings into the
calculation of the equivalent delay. The sender can react to these
explicit congestion signals without any modification.

Ultimately, networks equipped with proactive marking based on token
bucket level metering can reap the additional benefits of zero
standing queues and lower end-to-end delay and work seamlessly with
existing senders and receivers.

7. Implementation Status

The NADA scheme has been implemented in [ns-2] and [ns-3] simulation
platforms. Extensive ns-2 simulation evaluations of an earlier
version of the draft are documented in [Zhu-PV13]. Evaluation
results of the current draft over several test cases in
[I-D.ietf-rmcat-eval-test] have been presented at recent IETF
meetings [IETF-90][IETF-91]. Evaluation results of the current draft
over several test cases in [I-D.ietf-rmcat-wireless-tests] have been
presented at [IETF-93].





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The scheme has also been implemented and evaluated in a lab setting
as described in [IETF-90]. Preliminary evaluation results of NADA in
single-flow and multi-flow scenarios have been presented in
[IETF-91].

8. IANA Considerations

This document makes no request of IANA.

9. Acknowledgements

The authors would like to thank Randell Jesup, Luca De Cicco, Piers
O'Hanlon, Ingemar Johansson, Stefan Holmer, Cesar Ilharco Magalhaes,
Safiqul Islam, Mirja Kuhlewind, and Karen Elisabeth Egede Nielsen for
their valuable questions and comments on earlier versions of this
draft.

10. References

10.1. 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,
.

[RFC3168] Ramakrishnan, K., Floyd, S., and D. Black, "The Addition
of Explicit Congestion Notification (ECN) to IP",
RFC 3168, DOI 10.17487/RFC3168, September 2001,
.

[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, .

[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, .

[I-D.ietf-rmcat-eval-test]
Sarker, Z., Varun, V., Zhu, X., and M. Ramalho, "Test
Cases for Evaluating RMCAT Proposals", draft-ietf-rmcat-
eval-test-03 (work in progress), March 2016.






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[I-D.ietf-rmcat-cc-requirements]
Jesup, R. and Z. Sarker, "Congestion Control Requirements
for Interactive Real-Time Media", draft-ietf-rmcat-cc-
requirements-09 (work in progress), December 2014.

[I-D.ietf-rmcat-video-traffic-model]
Zhu, X., Cruz, S., and Z. Sarker, "Modeling Video Traffic
Sources for RMCAT Evaluations", draft-ietf-rmcat-video-
traffic-model-00 (work in progress), January 2016.

[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-wireless-tests]
Sarker, Z., Johansson, I., Zhu, X., Fu, J., Tan, W., and
M. Ramalho, "Evaluation Test Cases for Interactive Real-
Time Media over Wireless Networks", draft-ietf-rmcat-
wireless-tests-01 (work in progress), November 2015.

10.2. Informative References

[RFC2309] Braden, B., Clark, D., Crowcroft, J., Davie, B., Deering,
S., Estrin, D., Floyd, S., Jacobson, V., Minshall, G.,
Partridge, C., Peterson, L., Ramakrishnan, K., Shenker,
S., Wroclawski, J., and L. Zhang, "Recommendations on
Queue Management and Congestion Avoidance in the
Internet", RFC 2309, DOI 10.17487/RFC2309, April 1998,
.

[RFC5348] Floyd, S., Handley, M., Padhye, J., and J. Widmer, "TCP
Friendly Rate Control (TFRC): Protocol Specification",
RFC 5348, DOI 10.17487/RFC5348, September 2008,
.

[RFC6660] Briscoe, B., Moncaster, T., and M. Menth, "Encoding Three
Pre-Congestion Notification (PCN) States in the IP Header
Using a Single Diffserv Codepoint (DSCP)", RFC 6660,
DOI 10.17487/RFC6660, July 2012,
.

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




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[Floyd-CCR00]
Floyd, S., Handley, M., Padhye, J., and J. Widmer,
"Equation-based Congestion Control for Unicast
Applications", ACM SIGCOMM Computer Communications
Review vol. 30, no. 4, pp. 43-56, October 2000.

[Budzisz-TON11]
Budzisz, L., Stanojevic, R., Schlote, A., Baker, F., and
R. Shorten, "On the Fair Coexistence of Loss- and Delay-
Based TCP", IEEE/ACM Transactions on Networking vol. 19,
no. 6, pp. 1811-1824, December 2011.

[Zhu-PV13]
Zhu, X. and R. Pan, "NADA: A Unified Congestion Control
Scheme for Low-Latency Interactive Video", in Proc. IEEE
International Packet Video Workshop (PV'13) San Jose, CA,
USA, December 2013.

[ns-2] "The Network Simulator - ns-2",
.

[ns-3] "The Network Simulator - ns-3", .

[IETF-90] Zhu, X., Ramalho, M., Ganzhorn, C., Jones, P., and R. Pan,
"NADA Update: Algorithm, Implementation, and Test Case
Evalua6on Results", July 2014,
6.pdf>.

[IETF-91] Zhu, X., Pan, R., Ramalho, M., Mena, S., Ganzhorn, C.,
Jones, P., and S. D'Aronco, "NADA Algorithm Update and
Test Case Evaluations", November 2014,
slides/slides-interim-2014-rmcat-1-2.pdf>.

[IETF-93] Zhu, X., Pan, R., Ramalho, M., Mena, S., Ganzhorn, C.,
Jones, P., D'Aronco, S., and J. Fu, "Updates on NADA",
July 2015, slides-93-rmcat-0.pdf>.

Appendix A. Network Node Operations

NADA can work with different network queue management schemes and
does not assume any specific network node operation. As an example,
this appendix describes three variants of queue management behavior
at the network node, leading to either implicit or explicit
congestion signals.




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In all three flavors described below, the network queue operates with
the simple first-in-first-out (FIFO) principle. There is no need to
maintain per-flow state. The system can scale easily with a large
number of video flows and at high link capacity.

A.1. Default behavior of drop tail queues

In a conventional network with drop tail or RED queues, congestion is
inferred from the estimation of end-to-end delay and/or packet loss.
Packet drops at the queue are detected at the receiver, and
contributes to the calculation of the aggregated congestion signal
x_curr. No special action is required at network node.

A.2. RED-based ECN marking

In this mode, the network node randomly marks the ECN field in the IP
packet header following the Random Early Detection (RED) algorithm
[RFC2309]. Calculation of the marking probability involves the
following steps:

on packet arrival:
update smoothed queue size q_avg as:
q_avg = w*q + (1-w)*q_avg.

calculate marking probability p as:

/ 0, if q < q_lo;
|
| q_avg - q_lo
p= < p_max*--------------, if q_lo <= q < q_hi;
| q_hi - q_lo
|
\ p = 1, if q >= q_hi.

Here, q_lo and q_hi corresponds to the low and high thresholds of
queue occupancy. The maximum marking probability is p_max.

The ECN markings events will contribute to the calculation of an
equivalent delay x_curr at the receiver. No changes are required at
the sender.

A.3. Random Early Marking with Virtual Queues

Advanced network nodes may support random early marking based on a
token bucket algorithm originally designed for Pre-Congestion
Notification (PCN) [RFC6660]. The early congestion notification
(ECN) bit in the IP header of packets are marked randomly. The
marking probability is calculated based on a token-bucket algorithm



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originally designed for the Pre-Congestion Notification (PCN)
[RFC6660]. The target link utilization is set as 90%; the marking
probability is designed to grow linearly with the token bucket size
when it varies between 1/3 and 2/3 of the full token bucket limit.

* upon packet arrival, meter packet against token bucket (r,b);

* update token level b_tk;

* calculate the marking probability as:


/ 0, if b-b_tk < b_lo;
|
| b-b_tk-b_lo
p = < p_max* --------------, if b_lo<= b-b_tk | b_hi-b_lo
|
\ 1, if b-b_tk>=b_hi.


Here, the token bucket lower and upper limits are denoted by b_lo and
b_hi, respectively. The parameter b indicates the size of the token
bucket. The parameter r is chosen to be below capacity, resulting in
slight under-utilization of the link. The maximum marking
probability is p_max.

The ECN markings events will contribute to the calculation of an
equivalent delay x_curr at the receiver. No changes are required at
the sender. The virtual queuing mechanism from the PCN-based marking
algorithm will lead to additional benefits such as zero standing
queues.

Authors' Addresses

Xiaoqing Zhu
Cisco Systems
12515 Research Blvd., Building 4
Austin, TX 78759
USA

Email: xiaoqzhu@cisco.com









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Rong Pan
Cisco Systems
3625 Cisco Way
San Jose, CA 95134
USA

Email: ropan@cisco.com


Michael A. Ramalho
Cisco Systems, Inc.
8000 Hawkins Road
Sarasota, FL 34241
USA

Phone: +1 919 476 2038
Email: mramalho@cisco.com


Sergio Mena de la Cruz
Cisco Systems
EPFL, Quartier de l'Innovation, Batiment E
Ecublens, Vaud 1015
Switzerland

Email: semena@cisco.com


Paul E. Jones
Cisco Systems
7025 Kit Creek Rd.
Research Triangle Park, NC 27709
USA

Email: paulej@packetizer.com


Jiantao Fu
Cisco Systems
707 Tasman Drive
Milpitas, CA 95035
USA

Email: jianfu@cisco.com







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Stefano D'Aronco
Ecole Polytechnique Federale de Lausanne
EPFL STI IEL LTS4, ELD 220 (Batiment ELD), Station 11
Lausanne CH-1015
Switzerland

Email: stefano.daronco@epfl.ch


Charles Ganzhorn
7900 International Drive, International Plaza, Suite 400
Bloomington, MN 55425
USA

Email: charles.ganzhorn@gmail.com




































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