Internet DRAFT - draft-zhu-rmcat-nada
draft-zhu-rmcat-nada
Network Working Group X. Zhu, R. Pan
Internet Draft M. A. Ramalho, S. Mena
Intended Status: Informational C. Ganzhorn, P. E. Jones
Expires: September 27, 2015 Cisco Systems
S. De Aronco
Ecole Polytechnique Federale de Lausanne
March 26, 2015
NADA: A Unified Congestion Control Scheme for Real-Time Media
draft-zhu-rmcat-nada-06
Abstract
Network-Assisted Dynamic Adaptation (NADA) is a novel congestion
control scheme for interactive real-time media applications, such as
video conferencing. In NADA, the sender regulates its sending rate
based on either implicit or explicit congestion signaling in a
consistent manner. As one example of explicit signaling, NADA can
benefit from explicit congestion notification (ECN) markings from
network nodes. It also maintains consistent sender behavior in the
absence of explicit signaling by reacting to queuing delay and packet
loss.
This document describes the overall system architecture for NADA, as
well as recommended behavior at the sender and the receiver.
Status of this Memo
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Copyright and License Notice
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Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . 3
2. Terminology . . . . . . . . . . . . . . . . . . . . . . . . . . 3
3. System Model . . . . . . . . . . . . . . . . . . . . . . . . . 3
4. NADA Receiver Behavior . . . . . . . . . . . . . . . . . . . . 4
4.1 Estimation of one-way delay and queuing delay . . . . . . . 4
4.2 Estimation of packet loss/marking ratio . . . . . . . . . . 5
4.3 Non-linear warping of delay . . . . . . . . . . . . . . . . 6
4.4 Aggregating congestion signals . . . . . . . . . . . . . . . 7
4.5 Estimating receiving rate . . . . . . . . . . . . . . . . . 7
4.6 Sending periodic feedback . . . . . . . . . . . . . . . . . 7
4.7 Discussions on delay metrics . . . . . . . . . . . . . . . . 8
5. NADA Sender Behavior . . . . . . . . . . . . . . . . . . . . . 9
5.1 Reference rate calculation . . . . . . . . . . . . . . . . . 10
5.1.1 Accelerated ramp up . . . . . . . . . . . . . . . . . . 10
5.1.2. Gradual rate update . . . . . . . . . . . . . . . . . . 11
5.2 Video encoder rate control . . . . . . . . . . . . . . . . . 12
5.3 Rate shaping buffer . . . . . . . . . . . . . . . . . . . . 12
5.4 Adjusting video target rate and sending rate . . . . . . . . 12
6. Incremental Deployment . . . . . . . . . . . . . . . . . . . . 13
7. Implementation Status . . . . . . . . . . . . . . . . . . . . . 13
8. IANA Considerations . . . . . . . . . . . . . . . . . . . . . . 14
9. References . . . . . . . . . . . . . . . . . . . . . . . . . . 14
9.1 Normative References . . . . . . . . . . . . . . . . . . . 14
9.2 Informative References . . . . . . . . . . . . . . . . . . 14
Appendix A. Network Node Operations . . . . . . . . . . . . . . . 15
A.1 Default behavior of drop tail . . . . . . . . . . . . . . . 16
A.2 ECN marking . . . . . . . . . . . . . . . . . . . . . . . . 16
A.3 PCN marking . . . . . . . . . . . . . . . . . . . . . . . . 16
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . . 17
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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.
Based on the above considerations, this document describes a 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. In addition,
it supports weighted bandwidth sharing among competing video flows.
This documentation describes the overall system architecture,
recommended designs at the sender and receiver, as well as expected
network node operations. The signaling mechanism consists of standard
RTP timestamp [RFC3550] and standard RTCP feedback reports.
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 RFC 2119 [RFC2119].
3. System Model
The overall system consists of the following elements:
* Source media stream, in the form of consecutive raw video
frames and audio samples;
* Media encoder with rate control capabilities. It takes the
source media stream and encodes it to an RTP stream at a target
bit rate R_v. Note that the actual output rate from the encoder
R_o may fluctuate around the target R_v. Also, the encoder can
only change its rate at rather coarse time intervals, e.g., once
every 0.5 seconds.
* RTP sender, responsible for calculating the target bit rate
R_n 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_v, and for regulating the
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actual sending rate R_s accordingly. A rate shaping buffer is
employed to absorb the instantaneous difference between video
encoder output rate R_v and sending rate R_s. The buffer size
L_s, together with R_n, influences the calculation of actual
sending rate R_s and video encoder target rate R_v. The RTP
sender also generates RTP timestamp in outgoing packets.
* RTP receiver, responsible for measuring and estimating end-to-
end delay based on sender RTP timestamp. In the presence of
packet loss and ECN markings, it keeps track of packet loss and
ECN marking ratios. It calculates the equivalent delay x_n that
accounts for queuing delay, ECN marking, and packet loss, as
well as the derivative (i.e., rate of change) of this congestion
signal as x'_n. The receiver feeds both pieces of information
(x_n and x'_n) back to the sender via periodic RTCP reports.
* 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 RED-based
ECN marking, and PCN marking using a token bucket algorithm.
Note that network node operation is out of scope for the design
of NADA.
In the following, we will elaborate on the respective operations at the
NADA receiver and sender.
4. NADA Receiver Behavior
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.
4.1 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]. NADA 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.
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In mathematical terms, for packet n arriving at the receiver, one-way
delay is calculated as:
x_n = t_r,n - t_s,n,
where t_s,n and t_r,n are sender and receiver timestamps, respectively.
A real-world implementation should also properly handle practical issues
such as wrap-around in the value of x_n, which are omitted from the
above simple expression for brevity.
The base delay, d_f, is estimated as the minimum value of previously
observed x_n's over a relatively long period. This assumes that the
drift between sending and receiving clocks remains bounded by a small
value.
Correspondingly, the queuing delay experienced by the packet n is
estimated as:
d_n = x_n - d_f.
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. We denote the resulting
queuing delay value as d_hat_n.
Our current implementation employs a simple 5-point median filter over
per-packet queuing delay estimates, followed by an exponential smoothing
filter. We have found such relatively simple treatment to suffice 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.
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.
4.2 Estimation of packet loss/marking ratio
The receiver detects packet losses via gaps in the RTP sequence numbers
of received packets. It then calculates instantaneous packet loss ratio
as the ratio between the number of missing packets over the number of
total transmitted packets in the given time window (e.g., during the
most recent 500ms). This instantaneous value is passed over an
exponential smoothing filter, and the filtered result is reported back
to the sender as the observed packet loss ratio p_L.
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We note that more sophisticated methods in packet loss ratio
calculation, such as that adopted by TFRC [Floyd-CCR00], will likely be
beneficial. These alternatives are currently under investigation.
Estimation of packet marking ratio p_M, when ECN is enabled at
bottleneck network nodes along the path, will follow the same procedure
as above. Here it is assumed that ECN marking information at the IP
header are somehow passed along to the transport layer by the receiving
endpoint.
4.3 Non-linear warping of delay
In order for a delay-based flow to hold its ground and sustain a
reasonable share of bandwidth in the presence of a loss-based flow
(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.
Inspired by the delay-adaptive congestion window backoff policy in
[Budzisz-TON11] -- the work by itself is a window-based congestion
control scheme with fair coexistence with TCP -- we devise the following
non-linear warping of estimated queuing delay value:
d_tilde_n = (d_hat_n), if d_hat_n < d_th;
(d_max - d_hat_n)^4
d_tilde_n = d_th --------------------, if d_th<d_hat_n<d_max;
(d_max - d_th)^4
d_tilde_n = 0, if d_hat_n > d_max.
Here, the queuing delay value is unchanged when it is below the first
threshold d_th; it is discounted following a non-linear curve when its
value falls between d_th and d_max; above d_max, the high queuing delay
value no longer counts toward congestion control.
When queuing delay is in the range (0, d_th), NADA operates in pure
delay-based mode if no losses/markings are present. When queuing delay
exceeds d_max, NADA reacts to loss/marking only. In between d_th and
d_max, the sending rate will converge and stabilize at an operating
point with a fairly high queuing delay and non-zero packet loss ratio.
In our current implementation d_th is chosen as 50ms and d_max is chosen
as 400ms. The impact of the choice of d_th and d_max will be
investigated in future work.
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4.4 Aggregating congestion signals
The receiver aggregates all three forms of congestion signal in terms of
an equivalent delay:
x_n = d_tilde_n + p_M*d_M + p_L*d_L, (1)
where d_M is a prescribed fictitious delay value associated with ECN
markings (e.g., d_M = 200 ms), and d_L is a prescribed fictitious delay
value associated with packet losses (e.g., d_L = 1 second). By
introducing a large fictitious delay penalty for ECN marking and packet
loss, the proposed scheme leads to low end-to-end actual delay in the
presence of such events.
While the value of d_M and d_L 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 being studied.
In the absence of ECN marking from the network, the value of x_n falls
back to the observed queuing delay d_n for packet n when queuing delay
is low and no packets are lost over a lightly congested path. In that
case the algorithm operates in purely delay-based mode.
4.5 Estimating receiving rate
Estimation of receiving rate of the flow is fairly straightforward. NADA
maintains a recent observation window of 500ms, and simply divides the
total size of packets arriving during that window over the time span.
The receiving rate is denoted as R_r.
4.6 Sending periodic feedback
Periodically, the receiver feeds back a tuple of the most recent values
of <d_hat_n, x_n, x'_n, R_r> in RTCP feedback messages to aid the sender
in its calculation of target rate. The queuing delay value d_hat_n is
included along with the composite congestion signal x_n so that the
sender can decide whether the network is truly underutilized (see Sec.
6.1.1 Accelerated ramp-up).
The value of x'_n corresponds to the derivative (i.e., rate of change)
of the composite congestion signal:
x_n - x_(n-k)
x'_n = ---------------, (2)
delta
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where the interval between consecutive RTCP feedback messages is denoted
as delta. The packet indices corresponding to the current and previous
feedback are n and (n-k), respectively.
The choice of target feedback interval needs to strike the right balance
between timely feedback and low RTCP feedback message counts. Through
simulation studies and frequency-domain analysis, it was determined that
a feedback interval below 250ms will not break up the feedback control
loop of the NADA congestion control algorithm. Thus, it is recommended
to use a target feed interval of 100ms. This will result in a feedback
bandwidth of 16Kbps with 200 bytes per feedback message, less than 0.1%
overhead for a 1Mbps flow.
4.7 Discussions on 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 LEDBAT [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 queuing delay 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 RTT in lieu of OWD, assuming that per-packet ACKs
are available. The main drawback of this latter approach is that the
scheme will be confused by congestion 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 at the
sender. Therefore, comparing the pros and cons regarding which delay
metric to adopt can be kept as an orthogonal direction of
investigation.
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5. NADA Sender Behavior
Figure 1 provides a detailed view of the NADA sender. Upon receipt of an
RTCP report from the receiver, the NADA sender updates its calculation
of the reference rate R_n. It further adjusts both the target rate for
the live video encoder R_v and the sending rate R_s over the network
based on the updated value of R_n, as well as the size of the rate
shaping buffer.
In the following, we describe these modules in further detail, and
explain how they interact with each other.
--------------------
| |
| Reference Rate | <---- RTCP report
| Calculator |
| |
--------------------
|
| R_n
|
--------------------------
| |
| |
\ / \ /
-------------------- -----------------
| | | |
| Video Target | | Sending Rate |
| Rate Calculator | | Calculator |
| | | |
-------------------- -----------------
| /|\ /|\ |
R_v| | | |
| ----------------------- |
| | | R_s
------------ |L_s |
| | | |
| | R_o -------------- \|/
| Encoder |----------> | | | | | --------------->
| | | | | | | video packets
------------ --------------
Rate Shaping Buffer
Figure 1 NADA Sender Structure
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5.1 Reference rate calculation
The sender initializes the reference rate R_n as R-min by default, or to
a value specified by the upper-layer application. [Editor's note: should
proper choice of starting rate value be within the scope of the CC
solution? ]
The reference rate R_n is calculated based on receiver feedback
information regarding queuing delay d_tilde_n, composite congestion
signal x_n, its derivative x'_n, as well as the receiving rate R_r. The
sender switches between two modes of operation:
* Accelerated ramp up: if the reported queuing delay is close to
zero and both values of x_n and x'_n are close to zero,
indicating empty queues along the path of the flow and,
consequently, underutilized network bandwidth; or
* Gradual rate update: in all other conditions, whereby the
receiver reports on a standing or increasing/decreasing queue
and/or composite congestion signal.
5.1.1 Accelerated ramp up
In the absence of a non-zero congestion signal to guide the sending rate
calculation, the sender needs to ramp up its estimated bandwidth as
quickly as possible without introducing excessive queuing delay. Ideally
the flow should inflict no more than T_th milliseconds of queuing delay
at the bottleneck during the ramp-up process. A typical value of T_th is
50ms.
Note that the sender will be aware of any queuing delay introduced by
its rate increase after at least one round-trip time. In addition, the
bottleneck bandwidth C is greater than or equal to the receive rate R_r
reported from the most recent "no congestion" feedback message. The rate
R_n is updated as follows:
T_th
gamma = min [gamma_0, ---------------] (3)
RTT_0+delta_0
R_n = (1+gamma) R_r (4)
In (3) and (4), the multiplier gamma for rate increase is upper-bounded
by a fixed ratio gamma_0 (e.g., 20%), as well as a ratio which depends
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on T_th, base RTT as measured during the non-congested phase, and target
ACK interval delta_0. The rationale behind this is that the rate
increase multiplier should decrease with the delay in the feedback
control loop, and that RTT_0 + delta_0 provides a worst-case estimate of
feedback control delay when the network is not congested.
5.1.2. Gradual rate update
When the receiver reports indicate a standing congestion level, NADA
operates in gradual update mode, and calculates its reference rate as:
kappa * delta_s
R_n <-- R_n + ---------------- * (theta-(R_n-R_min)*x_hat) (5)
tau_o^2
where
theta = w*(R_max - R_min)*x_ref. (6)
x_hat = x_n + eta*tau_o* x'_n (7)
In (5), delta_s refers to the time interval between current and previous
rate updates. Note that delta_s is the same as the RTCP report interval
at the receiver (see delta from (2)) when the backward path is un-
congested.
In (6), R_min and R_max denote the content-dependent rate range the
encoder can produce. The weighting factor reflecting a flow's priority
is w. The reference congestion signal x_ref is chosen so that the
maximum rate of R_max can be achieved when x_hat = w*x_ref.
Proper choice of the scaling parameters eta and kappa in (5) and (7) can
ensure system stability so long as the RTT falls below the upper bound
of tau_o. The recommended default value of tau_o is chosen as 500ms.
For both modes of operations, the final reference rate R_n is clipped
within the range of [R_min, R_max]. Note also that the sender does not
need any explicit knowledge of the management scheme inside the network.
Rather, it reacts to the aggregation of all forms of congestion
indications (delay, loss, and explicit markings) via the composite
congestion signals x_n and x'_n from the receiver in a coherent manner.
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5.2 Video encoder rate control
The video encoder rate control procedure has the following
characteristics:
* Rate changes can happen only at large intervals, on the order of
seconds.
* The encoder output rate may fluctuate around the target rate R_v.
* The encoder output rate is further constrained by video content
complexity. The range of the final rate output is [R_min, R_max].
Note that it is content-dependent and may vary over time.
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.
5.3 Rate shaping buffer
A rate shaping buffer is employed to absorb any instantaneous mismatch
between encoder rate output R_o and regulated sending rate R_s. The size
of the buffer evolves from time t-tau to time t as:
L_s(t) = max [0, L_s(t-tau)+(R_o-R_s)*tau].
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 constrain the size of
the shaping buffer. It can either deplete it faster by increasing the
sending rate R_s, or limit its growth by reducing the target rate for
the video encoder rate control R_v.
5.4 Adjusting video target rate and sending rate
The target rate for the live video encoder is updated based on both the
reference rate R_n and the rate shaping buffer size L_s, as follows:
L_s
R_v = R_n - beta_v * -------. (8)
tau_v
Similarly, the outgoing rate is regulated based on both the reference
rate R_n and the rate shaping buffer size L_s, such that:
L_s
R_s = R_n + beta_s * -------. (9)
tau_v
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In (8) and (9), 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_n.
Intuitively, the amount of extra rate offset needed to completely drain
the rate shaping buffer within the same time frame of encoder rate
adaptation tau_v is given by L_s/tau_v. 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 the system from
the reference rate point.
6. 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 encoder 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 the ns-2 simulation platform
[ns2]. Extensive 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.draft-sarker-rmcat-eval-test] have
been presented at recent IETF meetings [IETF-90][IETF-91].
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].
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8. IANA Considerations
There are no actions for IANA.
9. References
9.1 Normative References
[RFC2119] Bradner, S., "Key words for use in RFCs to Indicate
Requirement Levels", BCP 14, RFC 2119, March 1997.
[RFC3168] Ramakrishnan, K., Floyd, S., and D. Black, "The Addition
of Explicit Congestion Notification (ECN) to IP",
RFC 3168, September 2001.
[RFC3550] Schulzrinne, H., Casner, S., Frederick, R., and V.
Jacobson, "RTP: A Transport Protocol for Real-Time
Applications", STD 64, RFC 3550, July 2003.
9.2 Informative References
[RFC3168] Ramakrishnan, K., Floyd, S., and D. Black, "The Addition
of Explicit Congestion Notification (ECN) to IP",
RFC 3168, September 2001.
[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, April 1998.
[RFC6817] Shalunov, S., Hazel, G., Iyengar, J., and Kuehlewind, M.,
"Low Extra Delay Background Transport (LEDBAT)", RFC 6817,
December 2012
[Floyd-CCR00] Floyd, S., Handley, M., Padhye, J., and Widmer, J.,
"Equation-based Congestion Control for Unicast
Applications", ACM SIGCOMM Computer Communications Review,
vol. 30. no. 4., pp. 43-56, October 2000.
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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
variations of queue management behavior at the network
node, leading to either implicit or explicit congestion
signals.
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.
Such a simple design ensures that the system can scale
easily with a large number of video flows and high link
capacity.
NADA sender behavior stays the same in the presence of all
types of congestion indicators: delay, loss, ECN marking
due to either RED/ECN or PCN algorithms. 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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A.1 Default behavior of drop tail
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 equivalent delay x_n. No special action
is required at network node.
A.2 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:
* upon packet arrival, update smoothed queue size q_avg as:
q_avg = alpha*q + (1-alpha)*q_avg.
The smoothing parameter alpha is a value between 0 and 1. A value of
alpha=1 corresponds to performing no smoothing at all.
* calculate marking probability p as:
p = 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_n at the receiver. No changes are required at the
sender.
A.3 PCN marking
As a more advanced feature, we also envisage network nodes which support
PCN marking based on virtual queues. In such a case, the marking
probability of the ECN bit in the IP packet header is calculated as
follows:
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* upon packet arrival, meter packet against token bucket (r,b);
* update token level b_tk;
* calculate the marking probability as:
p = 0, if b-b_tk < b_lo;
b-b_tk-b_lo
p = p_max* --------------, if b_lo<= b-b_tk <b_hi;
b_hi-b_lo
p = 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 as r=gamma*C, where gamma<1 is the
target utilization ratio and C designates link capacity. The maximum
marking probability is p_max.
The ECN markings events will contribute to the calculation of an
equivalent delay x_n at the receiver. No changes are required at the
sender. The virtual queuing mechanism from the PCN marking algorithm
will lead to additional benefits such as zero standing queues.
Authors' Addresses
Xiaoqing Zhu
Cisco Systems,
12515 Research Blvd.,
Austin, TX 78759, USA
Email: xiaoqzhu@cisco.com
Rong Pan
Cisco Systems
510 McCarthy Blvd,
Milpitas, CA 95134, USA
Email: ropan@cisco.com
Michael A. Ramalho
6310 Watercrest Way Unit 203
Lakewood Ranch, FL, 34202, USA
Email: mramalho@cisco.com
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Sergio Mena de la Cruz
Cisco Systems
EPFL, Quartier de l'Innovation, Batiment E
Ecublens, Vaud 1015, Switzerland
Email: semena@cisco.com
Charles Ganzhorn
7900 International Drive
International Plaza, Suite 400
Bloomington, MN 55425, USA
Email: charles.ganzhorn@gmail.com
Paul E. Jones
7025 Kit Creek Rd.
Research Triangle Park, NC 27709, USA
Email: paulej@packetizer.com
Stefano D'Aronco
EPFL STI IEL LTS4
ELD 220 (Batiment ELD), Station 11
CH-1015 Lausanne, Switzerland
Email: stefano.daronco@epfl.ch
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