Internet DRAFT - draft-eggert-tcpm-rfc8312bis
draft-eggert-tcpm-rfc8312bis
TCPM L. Xu
Internet-Draft UNL
Obsoletes: 8312 (if approved) S. Ha
Intended status: Standards Track Colorado
Expires: 11 September 2021 I. Rhee
Bowery
V. Goel
Apple Inc.
L. Eggert, Ed.
NetApp
10 March 2021
CUBIC for Fast and Long-Distance Networks
draft-eggert-tcpm-rfc8312bis-03
Abstract
CUBIC is an extension to the traditional TCP standards. It differs
from the traditional TCP standards only in the congestion control
algorithm on the sender side. In particular, it uses a cubic
function instead of the linear window increase function of the
traditional TCP standards to improve scalability and stability under
fast and long-distance networks. CUBIC has been adopted as the
default TCP congestion control algorithm by the Linux, Windows, and
Apple stacks.
This document updates the specification of CUBIC to include
algorithmic improvements based on these implementations and recent
academic work. Based on the extensive deployment experience with
CUBIC, it also moves the specification to the Standards Track,
obsoleting [RFC8312].
Note to Readers
Discussion of this draft takes place on the TCPM working group
mailing list (mailto:tcpm@ietf.org), which is archived at
https://mailarchive.ietf.org/arch/browse/tcpm/.
Working Group information can be found at
https://datatracker.ietf.org/wg/tcpm/; source code and issues list
for this draft can be found at https://github.com/NTAP/rfc8312bis.
Status of This Memo
This Internet-Draft is submitted in full conformance with the
provisions of BCP 78 and BCP 79.
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Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 3
2. Conventions . . . . . . . . . . . . . . . . . . . . . . . . . 4
3. Design Principles of CUBIC . . . . . . . . . . . . . . . . . 4
3.1. Principle 1 for the CUBIC Increase Function . . . . . . . 5
3.2. Principle 2 for AIMD Friendliness . . . . . . . . . . . . 6
3.3. Principle 3 for RTT Fairness . . . . . . . . . . . . . . 6
3.4. Principle 4 for the CUBIC Decrease Factor . . . . . . . . 7
4. CUBIC Congestion Control . . . . . . . . . . . . . . . . . . 7
4.1. Definitions . . . . . . . . . . . . . . . . . . . . . . . 7
4.1.1. Constants of Interest . . . . . . . . . . . . . . . . 7
4.1.2. Variables of Interest . . . . . . . . . . . . . . . . 8
4.2. Window Increase Function . . . . . . . . . . . . . . . . 9
4.3. AIMD-Friendly Region . . . . . . . . . . . . . . . . . . 10
4.4. Concave Region . . . . . . . . . . . . . . . . . . . . . 12
4.5. Convex Region . . . . . . . . . . . . . . . . . . . . . . 12
4.6. Multiplicative Decrease . . . . . . . . . . . . . . . . . 13
4.7. Fast Convergence . . . . . . . . . . . . . . . . . . . . 13
4.8. Timeout . . . . . . . . . . . . . . . . . . . . . . . . . 14
4.9. Spurious Congestion Events . . . . . . . . . . . . . . . 14
4.10. Slow Start . . . . . . . . . . . . . . . . . . . . . . . 16
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5. Discussion . . . . . . . . . . . . . . . . . . . . . . . . . 16
5.1. Fairness to AIMD TCP . . . . . . . . . . . . . . . . . . 17
5.2. Using Spare Capacity . . . . . . . . . . . . . . . . . . 19
5.3. Difficult Environments . . . . . . . . . . . . . . . . . 20
5.4. Investigating a Range of Environments . . . . . . . . . . 20
5.5. Protection against Congestion Collapse . . . . . . . . . 21
5.6. Fairness within the Alternative Congestion Control
Algorithm . . . . . . . . . . . . . . . . . . . . . . . 21
5.7. Performance with Misbehaving Nodes and Outside
Attackers . . . . . . . . . . . . . . . . . . . . . . . 21
5.8. Behavior for Application-Limited Flows . . . . . . . . . 21
5.9. Responses to Sudden or Transient Events . . . . . . . . . 21
5.10. Incremental Deployment . . . . . . . . . . . . . . . . . 21
6. Security Considerations . . . . . . . . . . . . . . . . . . . 21
7. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 22
8. References . . . . . . . . . . . . . . . . . . . . . . . . . 22
8.1. Normative References . . . . . . . . . . . . . . . . . . 22
8.2. Informative References . . . . . . . . . . . . . . . . . 23
Appendix A. Acknowledgements . . . . . . . . . . . . . . . . . . 25
Appendix B. Evolution of CUBIC . . . . . . . . . . . . . . . . . 25
B.1. Since draft-eggert-tcpm-rfc8312bis-02 . . . . . . . . . . 25
B.2. Since draft-eggert-tcpm-rfc8312bis-01 . . . . . . . . . . 25
B.3. Since draft-eggert-tcpm-rfc8312bis-00 . . . . . . . . . . 26
B.4. Since RFC8312 . . . . . . . . . . . . . . . . . . . . . . 26
B.5. Since the Original Paper . . . . . . . . . . . . . . . . 27
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 27
1. Introduction
The low utilization problem of traditional TCP in fast and long-
distance networks is well documented in [K03] and [RFC3649]. This
problem arises from a slow increase of the congestion window
following a congestion event in a network with a large bandwidth-
delay product (BDP). [HKLRX06] indicates that this problem is
frequently observed even in the range of congestion window sizes over
several hundreds of packets. This problem is equally applicable to
all Reno-style TCP standards and their variants, including TCP-Reno
[RFC5681], TCP-NewReno [RFC6582][RFC6675], SCTP [RFC4960], and TFRC
[RFC5348], which use the same linear increase function for window
growth. We refer to all Reno-style TCP standards and their variants
collectively as "AIMD TCP" below because they use the Additive
Increase and Multiplicative Decrease algorithm (AIMD).
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CUBIC, originally proposed in [HRX08], is a modification to the
congestion control algorithm of traditional AIMD TCP to remedy this
problem. This document describes the most recent specification of
CUBIC. Specifically, CUBIC uses a cubic function instead of the
linear window increase function of AIMD TCP to improve scalability
and stability under fast and long-distance networks.
Binary Increase Congestion Control (BIC-TCP) [XHR04], a predecessor
of CUBIC, was selected as the default TCP congestion control
algorithm by Linux in the year 2005 and had been used for several
years by the Internet community at large.
CUBIC uses a similar window increase function as BIC-TCP and is
designed to be less aggressive and fairer to AIMD TCP in bandwidth
usage than BIC-TCP while maintaining the strengths of BIC-TCP such as
stability, window scalability, and round-trip time (RTT) fairness.
CUBIC has been adopted as the default TCP congestion control
algorithm in the Linux, Windows, and Apple stacks, and has been used
and deployed globally. Extensive, decade-long deployment experience
in vastly different Internet scenarios has convincingly demonstrated
that CUBIC is safe for deployment on the global Internet and delivers
substantial benefits over traditional AIMD congestion control. It is
therefore to be regarded as the current standard for TCP congestion
control.
In the following sections, we first briefly explain the design
principles of CUBIC, then provide the exact specification of CUBIC,
and finally discuss the safety features of CUBIC following the
guidelines specified in [RFC5033].
2. Conventions
The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT",
"SHOULD", "SHOULD NOT", "RECOMMENDED", "NOT RECOMMENDED", "MAY", and
"OPTIONAL" in this document are to be interpreted as described in
BCP 14 [RFC2119] [RFC8174] when, and only when, they appear in all
capitals, as shown here.
3. Design Principles of CUBIC
CUBIC is designed according to the following design principles:
Principle 1: For better network utilization and stability, CUBIC
uses both the concave and convex profiles of a cubic function to
increase the congestion window size, instead of using just a
convex function.
Principle 2: To be AIMD-friendly, CUBIC is designed to behave like
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AIMD TCP in networks with short RTTs and small bandwidth where
AIMD TCP performs well.
Principle 3: For RTT-fairness, CUBIC is designed to achieve linear
bandwidth sharing among flows with different RTTs.
Principle 4: CUBIC appropriately sets its multiplicative window
decrease factor in order to balance between the scalability and
convergence speed.
3.1. Principle 1 for the CUBIC Increase Function
For better network utilization and stability, CUBIC [HRX08] uses a
cubic window increase function in terms of the elapsed time from the
last congestion event. While most alternative congestion control
algorithms to AIMD TCP increase the congestion window using convex
functions, CUBIC uses both the concave and convex profiles of a cubic
function for window growth.
After a window reduction in response to a congestion event is
detected by duplicate ACKs or Explicit Congestion Notification-Echo
(ECN-Echo, ECE) ACKs [RFC3168], CUBIC remembers the congestion window
size where it received the congestion event and performs a
multiplicative decrease of the congestion window. When CUBIC enters
into congestion avoidance, it starts to increase the congestion
window using the concave profile of the cubic function. The cubic
function is set to have its plateau at the remembered congestion
window size, so that the concave window increase continues until
then. After that, the cubic function turns into a convex profile and
the convex window increase begins.
This style of window adjustment (concave and then convex) improves
the algorithm stability while maintaining high network utilization
[CEHRX07]. This is because the window size remains almost constant,
forming a plateau around the remembered congestion window size of the
last congestion event, where network utilization is deemed highest.
Under steady state, most window size samples of CUBIC are close to
that remembered congestion window size, thus promoting high network
utilization and stability.
Note that congestion control algorithms that only use convex
functions to increase the congestion window size have their maximum
increments around the remembered congestion window size of the last
congestion event, and thus introduce a large number of packet bursts
around the saturation point of the network, likely causing frequent
global loss synchronizations.
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3.2. Principle 2 for AIMD Friendliness
CUBIC promotes per-flow fairness to AIMD TCP. Note that AIMD TCP
performs well over paths with short RTTs and small bandwidths (or
small BDPs). There is only a scalability problem in networks with
long RTTs and large bandwidths (or large BDPs).
A congestion control algorithm designed to be friendly to AIMD TCP on
a per-flow basis must increase its congestion window less
aggressively in small BDP networks than in large BDP networks.
The aggressiveness of CUBIC mainly depends on the maximum window size
before a window reduction, which is smaller in small-BDP networks
than in large-BDP networks. Thus, CUBIC increases its congestion
window less aggressively in small-BDP networks than in large-BDP
networks.
Furthermore, in cases when the cubic function of CUBIC would increase
the congestion window less aggressively than AIMD TCP, CUBIC simply
follows the window size of AIMD TCP to ensure that CUBIC achieves at
least the same throughput as AIMD TCP in small-BDP networks. We call
this region where CUBIC behaves like AIMD TCP the "AIMD-friendly
region".
3.3. Principle 3 for RTT Fairness
Two CUBIC flows with different RTTs have a throughput ratio that is
linearly proportional to the inverse of their RTT ratio, where the
throughput of a flow is approximately the size of its congestion
window divided by its RTT.
Specifically, CUBIC maintains a window increase rate independent of
RTTs outside of the AIMD-friendly region, and thus flows with
different RTTs have similar congestion window sizes under steady
state when they operate outside the AIMD-friendly region.
This notion of a linear throughput ratio is similar to that of AIMD
TCP under high statistical multiplexing where packet loss is
independent of individual flow rates. However, under low statistical
multiplexing, the throughput ratio of AIMD TCP flows with different
RTTs is quadratically proportional to the inverse of their RTT ratio
[XHR04].
CUBIC always ensures a linear throughput ratio independent of the
amount of statistical multiplexing. This is an improvement over AIMD
TCP. While there is no consensus on particular throughput ratios for
different RTT flows, we believe that over wired Internet paths, use
of a linear throughput ratio seems more reasonable than equal
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throughputs (i.e., the same throughput for flows with different RTTs)
or a higher-order throughput ratio (e.g., a quadratical throughput
ratio of AIMD TCP under low statistical multiplexing environments).
3.4. Principle 4 for the CUBIC Decrease Factor
To balance between scalability and convergence speed, CUBIC sets the
multiplicative window decrease factor to 0.7, whereas AIMD TCP uses
0.5.
While this improves the scalability of CUBIC, a side effect of this
decision is slower convergence, especially under low statistical
multiplexing. This design choice is following the observation that
HighSpeed TCP (HSTCP) [RFC3649] and other approaches (e.g., [GV02])
made: the current Internet becomes more asynchronous with less
frequent loss synchronizations under high statistical multiplexing.
In such environments, even strict Multiplicative-Increase
Multiplicative-Decrease (MIMD) can converge. CUBIC flows with the
same RTT always converge to the same throughput independent of
statistical multiplexing, thus achieving intra-algorithm fairness.
We also find that in environments with sufficient statistical
multiplexing, the convergence speed of CUBIC is reasonable.
4. CUBIC Congestion Control
In this section, we discuss how the congestion window is updated
during the different stages of the CUBIC congestion controller.
4.1. Definitions
The unit of all window sizes in this document is segments of the
maximum segment size (MSS), and the unit of all times is seconds.
4.1.1. Constants of Interest
β__(cubic)_: CUBIC multiplication decrease factor as described in
Section 4.6.
α__(aimd)_: CUBIC additive increase factor used in AIMD-friendly
region as described in Section 4.3.
_C_: constant that determines the aggressiveness of CUBIC in
competing with other congestion control algorithms in high BDP
networks. Please see Section 5 for more explanation on how it is
set. The unit for _C_ is
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segment
-------
3
second
4.1.2. Variables of Interest
This section defines the variables required to implement CUBIC:
_RTT_: Smoothed round-trip time in seconds, calculated as described
in [RFC6298].
_cwnd_: Current congestion window in segments.
_ssthresh_: Current slow start threshold in segments.
_W_(max)_: Size of _cwnd_ in segments just before _cwnd_ was reduced
in the last congestion event.
_K_: The time period in seconds it takes to increase the congestion
window size at the beginning of the current congestion avoidance
stage to _W_(max)_.
_current_time_: Current time of the system in seconds.
_epoch_(start)_: The time in seconds at which the current congestion
avoidance stage started.
_cwnd_(start)_: The _cwnd_ at the beginning of the current congestion
avoidance stage, i.e., at time _epoch_(start)_.
W_(cubic)(_t_): The congestion window in segments at time _t_ in
seconds based on the cubic increase function, as described in
Section 4.2.
_target_: Target value of congestion window in segments after the
next RTT, that is, W_(cubic)(_t_ + _RTT_), as described in
Section 4.2.
_W_(est)_: An estimate for the congestion window in segments in the
AIMD-friendly region, that is, an estimate for the congestion window
of AIMD TCP.
_segments_acked_: Number of segments acked when an ACK is received.
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4.2. Window Increase Function
CUBIC maintains the acknowledgment (ACK) clocking of AIMD TCP by
increasing the congestion window only at the reception of an ACK. It
does not make any changes to the TCP Fast Recovery and Fast
Retransmit algorithms [RFC6582][RFC6675].
During congestion avoidance after a congestion event where a packet
loss is detected by duplicate ACKs or by receiving packets carrying
ECE flags [RFC3168], CUBIC changes the window increase function of
AIMD TCP.
CUBIC uses the following window increase function:
3
W (t) = C * (t - K) + W
cubic max
Figure 1
where _t_ is the elapsed time in seconds from the beginning of the
current congestion avoidance stage, that is,
t = current_time - epoch
start
and where _epoch_(start)_ is the time at which the current congestion
avoidance stage starts. _K_ is the time period that the above
function takes to increase the congestion window size at the
beginning of the current congestion avoidance stage to _W_(max)_ if
there are no further congestion events and is calculated using the
following equation:
________________
/W - cwnd
3 / max start
K = | / ----------------
|/ C
Figure 2
where _cwnd_(start)_ is the congestion window at the beginning of the
current congestion avoidance stage. For example, right after a
congestion event, _cwnd_(start)_ is equal to the new cwnd calculated
as described in Section 4.6.
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Upon receiving an ACK during congestion avoidance, CUBIC computes the
_target_ congestion window size after the next _RTT_ using Figure 1
as follows, where _RTT_ is the smoothed round-trip time. The lower
and upper bounds below ensure that CUBIC's congestion window increase
rate is non-decreasing and is less than the increase rate of slow
start.
/
| if W (t + RTT) < cwnd
|cwnd cubic
|
|
|
target = < if W (t + RTT) > 1.5 * cwnd
|1.5 * cwnd cubic
|
|
|W (t + RTT)
| cubic otherwise
\
Depending on the value of the current congestion window size _cwnd_,
CUBIC runs in three different regions:
1. The AIMD-friendly region, which ensures that CUBIC achieves at
least the same throughput as AIMD TCP.
2. The concave region, if CUBIC is not in the AIMD-friendly region
and _cwnd_ is less than _W_(max)_.
3. The convex region, if CUBIC is not in the AIMD-friendly region
and _cwnd_ is greater than _W_(max)_.
Below, we describe the exact actions taken by CUBIC in each region.
4.3. AIMD-Friendly Region
AIMD TCP performs well in certain types of networks, for example,
under short RTTs and small bandwidths (or small BDPs). In these
networks, CUBIC remains in the AIMD-friendly region to achieve at
least the same throughput as AIMD TCP.
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The AIMD-friendly region is designed according to the analysis in
[FHP00], which studies the performance of an AIMD algorithm with an
additive factor of α__(aimd)_ (segments per _RTT_) and a
multiplicative factor of β__(aimd)_, denoted by AIMD(α__(aimd)_,
β__(aimd)_). Specifically, the average congestion window size of
AIMD(α__(aimd)_, β__(aimd)_) can be calculated using Figure 3. The
analysis shows that AIMD(α__(aimd)_, β__(aimd)_) with
1 - β
cubic
α = 3 * ----------
aimd 1 + β
cubic
achieves the same average window size as AIMD TCP that uses AIMD(1,
0.5).
___________________
/α * (1 + β )
/ aimd aimd
AVG_AIMD(α , β ) = | / -------------------
aimd aimd | / 2 * (1 - β ) * p
|/ aimd
Figure 3
Based on the above analysis, CUBIC uses Figure 4 to estimate the
window size _W_(est)_ of AIMD(α__(aimd)_, β__(aimd)_) with
1 - β
cubic
α = 3 * ----------
aimd 1 + β
cubic
β = β
aimd cubic
which achieves the same average window size as AIMD TCP. When
receiving an ACK in congestion avoidance (where _cwnd_ could be
greater than or less than _W_(max)_), CUBIC checks whether
W_(cubic)(_t_) is less than _W_(est)_. If so, CUBIC is in the AIMD-
friendly region and _cwnd_ SHOULD be set to _W_(est)_ at each
reception of an ACK.
_W_(est)_ is set equal to _cwnd_(start)_ at the start of the
congestion avoidance stage. After that, on every ACK, _W_(est)_ is
updated using Figure 4.
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segments_acked
W = W + α * --------------
est est aimd cwnd
Figure 4
Note that once _W_(est)_ reaches _W_(max)_, that is, _W_(est)_ >=
_W_(max)_, α__(aimd)_ SHOULD be set to 1 to achieve the same
congestion window increment as AIMD TCP, which uses AIMD(1, 0.5).
4.4. Concave Region
When receiving an ACK in congestion avoidance, if CUBIC is not in the
AIMD-friendly region and _cwnd_ is less than _W_(max)_, then CUBIC is
in the concave region. In this region, _cwnd_ MUST be incremented by
target - cwnd
-------------
cwnd
for each received ACK, where _target_ is calculated as described in
Section 4.2.
4.5. Convex Region
When receiving an ACK in congestion avoidance, if CUBIC is not in the
AIMD-friendly region and _cwnd_ is larger than or equal to _W_(max)_,
then CUBIC is in the convex region.
The convex region indicates that the network conditions might have
changed since the last congestion event, possibly implying more
available bandwidth after some flow departures. Since the Internet
is highly asynchronous, some amount of perturbation is always
possible without causing a major change in available bandwidth.
In this region, CUBIC is very careful. The convex profile ensures
that the window increases very slowly at the beginning and gradually
increases its increase rate. We also call this region the "maximum
probing phase", since CUBIC is searching for a new _W_(max)_. In this
region, _cwnd_ MUST be incremented by
target - cwnd
-------------
cwnd
for each received ACK, where _target_ is calculated as described in
Section 4.2.
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4.6. Multiplicative Decrease
When a packet loss is detected by duplicate ACKs or by receiving
packets carrying ECE flags, CUBIC updates _W_(max)_ and reduces
_cwnd_ and _ssthresh_ immediately as described below. An
implementation MAY set a smaller _ssthresh_ than suggested below to
accomodate rate-limited applications as described in [RFC7661]. For
both packet loss and congestion detection through ECN, the sender MAY
employ a Fast Recovery algorithm to gradually adjust the congestion
window to its new reduced _ssthresh_ value. The parameter
β__(cubic)_ SHOULD be set to 0.7.
ssthresh = cwnd * β // new slow-start threshold
cubic
ssthresh = max(ssthresh, 2) // threshold is at least 2 MSS
// window reduction
cwnd = ssthresh
A side effect of setting β__(cubic)_ to a value bigger than 0.5 is
slower convergence. We believe that while a more adaptive setting of
β__(cubic)_ could result in faster convergence, it will make the
analysis of CUBIC much harder.
4.7. Fast Convergence
To improve convergence speed, CUBIC uses a heuristic. When a new
flow joins the network, existing flows need to give up some of their
bandwidth to allow the new flow some room for growth, if the existing
flows have been using all the network bandwidth. To speed up this
bandwidth release by existing flows, the following "Fast Convergence"
mechanism SHOULD be implemented.
With Fast Convergence, when a congestion event occurs, we update
_W_(max)_ as follows, before the window reduction as described in
Section 4.6.
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/
| 1 + β
| cubic if cwnd < W and fast convergence is enabled,
|cwnd * ---------- max
| 2
W = <
max | further reduce W
| max
|
| otherwise, remember cwnd before reduction
\cwnd
At a congestion event, if the current _cwnd_ is less than _W_(max)_,
this indicates that the saturation point experienced by this flow is
getting reduced because of a change in available bandwidth. Then we
allow this flow to release more bandwidth by reducing _W_(max)_
further. This action effectively lengthens the time for this flow to
increase its congestion window, because the reduced _W_(max)_ forces
the flow to plateau earlier. This allows more time for the new flow
to catch up to its congestion window size.
Fast Convergence is designed for network environments with multiple
CUBIC flows. In network environments with only a single CUBIC flow
and without any other traffic, Fast Convergence SHOULD be disabled.
4.8. Timeout
In case of a timeout, CUBIC follows AIMD TCP to reduce _cwnd_
[RFC5681], but sets _ssthresh_ using β__(cubic)_ (same as in
Section 4.6) in a way that is different from AIMD TCP [RFC5681].
During the first congestion avoidance stage after a timeout, CUBIC
increases its congestion window size using Figure 1, where _t_ is the
elapsed time since the beginning of the current congestion avoidance,
_K_ is set to 0, and _W_(max)_ is set to the congestion window size
at the beginning of the current congestion avoidance stage. In
addition, for the AIMD-friendly region, _W_(est)_ SHOULD be set to
the congestion window size at the beginning of the current congestion
avoidance.
4.9. Spurious Congestion Events
In cases where CUBIC reduces its congestion window in response to
having detected packet loss via duplicate ACKs or timeouts, there is
a possibility that the missing ACK would arrive after the congestion
window reduction and a corresponding packet retransmission. For
example, packet reordering could trigger this behavior. A high
degree of packet reordering could cause multiple congestion window
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reduction events, where spurious losses are incorrectly interpreted
as congestion signals, thus degrading CUBIC's performance
significantly.
When there is a congestion event, a CUBIC implementation SHOULD save
the current value of the following variables before the congestion
window reduction.
prior_cwnd = cwnd
prior_ssthresh = ssthresh
prior_W = W
max max
prior_K = K
prior_epoch = epoch
start start
prior_W_{est} = W
est
CUBIC MAY implement an algorithm to detect spurious retransmissions,
such as DSACK [RFC3708], Forward RTO-Recovery [RFC5682] or Eifel
[RFC3522]. Once a spurious congestion event is detected, CUBIC
SHOULD restore the original values of above mentioned variables as
follows if the current _cwnd_ is lower than _prior_cwnd_. Restoring
the original values ensures that CUBIC's performance is similar to
what it would be without spurious losses.
\
cwnd = prior_cwnd |
|
ssthresh = prior_ssthresh |
|
W = prior_W |
max max |
>if cwnd < prior_cwnd
K = prior_K |
|
epoch = prior_epoch |
start start|
|
W = prior_W |
est est /
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In rare cases, when the detection happens long after a spurious loss
event and the current _cwnd_ is already higher than _prior_cwnd_,
CUBIC SHOULD continue to use the current and the most recent values
of these variables.
4.10. Slow Start
CUBIC MUST employ a slow-start algorithm, when _cwnd_ is no more than
_ssthresh_. Among the slow-start algorithms, CUBIC MAY choose the
AIMD TCP slow start [RFC5681] in general networks, or the limited
slow start [RFC3742] or hybrid slow start [HR08] for fast and long-
distance networks.
When CUBIC uses hybrid slow start [HR08], it may exit the first slow
start without incurring any packet loss and thus _W_(max)_ is
undefined. In this special case, CUBIC switches to congestion
avoidance and increases its congestion window size using Figure 1,
where _t_ is the elapsed time since the beginning of the current
congestion avoidance, _K_ is set to 0, and _W_(max)_ is set to the
congestion window size at the beginning of the current congestion
avoidance stage.
5. Discussion
In this section, we further discuss the safety features of CUBIC
following the guidelines specified in [RFC5033].
With a deterministic loss model where the number of packets between
two successive packet losses is always _1/p_, CUBIC always operates
with the concave window profile, which greatly simplifies the
performance analysis of CUBIC. The average window size of CUBIC can
be obtained by the following function:
________________ ____
/C * (3 + β ) 3 / 4
4 / cubic |/ RTT
AVG_W = | / ---------------- * -------
cubic | / 4 * (1 - β ) __
|/ cubic 3 / 4
|/ p
Figure 5
With β__(cubic)_ set to 0.7, the above formula reduces to:
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____
_______ 3 / 4
4 /C * 3.7 |/ RTT
AVG_W = | / ------- * -------
cubic |/ 1.2 __
3 / 4
|/ p
Figure 6
We will determine the value of _C_ in the following subsection using
Figure 6.
5.1. Fairness to AIMD TCP
In environments where AIMD TCP is able to make reasonable use of the
available bandwidth, CUBIC does not significantly change this state.
AIMD TCP performs well in the following two types of networks:
1. networks with a small bandwidth-delay product (BDP)
2. networks with a short RTTs, but not necessarily a small BDP
CUBIC is designed to behave very similarly to AIMD TCP in the above
two types of networks. The following two tables show the average
window sizes of AIMD TCP, HSTCP, and CUBIC. The average window sizes
of AIMD TCP and HSTCP are from [RFC3649]. The average window size of
CUBIC is calculated using Figure 6 and the CUBIC AIMD-friendly region
for three different values of _C_.
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+=============+=======+========+================+=========+========+
| Loss Rate P | AIMD | HSTCP | CUBIC (C=0.04) | CUBIC | CUBIC |
| | | | | (C=0.4) | (C=4) |
+=============+=======+========+================+=========+========+
| 1.0e-02 | 12 | 12 | 12 | 12 | 12 |
+-------------+-------+--------+----------------+---------+--------+
| 1.0e-03 | 38 | 38 | 38 | 38 | 59 |
+-------------+-------+--------+----------------+---------+--------+
| 1.0e-04 | 120 | 263 | 120 | 187 | 333 |
+-------------+-------+--------+----------------+---------+--------+
| 1.0e-05 | 379 | 1795 | 593 | 1054 | 1874 |
+-------------+-------+--------+----------------+---------+--------+
| 1.0e-06 | 1200 | 12280 | 3332 | 5926 | 10538 |
+-------------+-------+--------+----------------+---------+--------+
| 1.0e-07 | 3795 | 83981 | 18740 | 33325 | 59261 |
+-------------+-------+--------+----------------+---------+--------+
| 1.0e-08 | 12000 | 574356 | 105383 | 187400 | 333250 |
+-------------+-------+--------+----------------+---------+--------+
Table 1: AIMD TCP, HSTCP, and CUBIC with RTT = 0.1 seconds
Table 1 describes the response function of AIMD TCP, HSTCP, and CUBIC
in networks with _RTT_ = 0.1 seconds. The average window size is in
MSS-sized segments.
+=============+=======+========+================+=========+=======+
| Loss Rate P | AIMD | HSTCP | CUBIC (C=0.04) | CUBIC | CUBIC |
| | | | | (C=0.4) | (C=4) |
+=============+=======+========+================+=========+=======+
| 1.0e-02 | 12 | 12 | 12 | 12 | 12 |
+-------------+-------+--------+----------------+---------+-------+
| 1.0e-03 | 38 | 38 | 38 | 38 | 38 |
+-------------+-------+--------+----------------+---------+-------+
| 1.0e-04 | 120 | 263 | 120 | 120 | 120 |
+-------------+-------+--------+----------------+---------+-------+
| 1.0e-05 | 379 | 1795 | 379 | 379 | 379 |
+-------------+-------+--------+----------------+---------+-------+
| 1.0e-06 | 1200 | 12280 | 1200 | 1200 | 1874 |
+-------------+-------+--------+----------------+---------+-------+
| 1.0e-07 | 3795 | 83981 | 3795 | 5926 | 10538 |
+-------------+-------+--------+----------------+---------+-------+
| 1.0e-08 | 12000 | 574356 | 18740 | 33325 | 59261 |
+-------------+-------+--------+----------------+---------+-------+
Table 2: AIMD TCP, HSTCP, and CUBIC with RTT = 0.01 seconds
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Table 2 describes the response function of AIMD TCP, HSTCP, and CUBIC
in networks with _RTT_ = 0.01 seconds. The average window size is in
MSS-sized segments.
Both tables show that CUBIC with any of these three _C_ values is
more friendly to AIMD TCP than HSTCP, especially in networks with a
short _RTT_ where AIMD TCP performs reasonably well. For example, in
a network with _RTT_ = 0.01 seconds and p=10^-6, AIMD TCP has an
average window of 1200 packets. If the packet size is 1500 bytes,
then AIMD TCP can achieve an average rate of 1.44 Gbps. In this
case, CUBIC with _C_=0.04 or _C_=0.4 achieves exactly the same rate
as AIMD TCP, whereas HSTCP is about ten times more aggressive than
AIMD TCP.
We can see that _C_ determines the aggressiveness of CUBIC in
competing with other congestion control algorithms for bandwidth.
CUBIC is more friendly to AIMD TCP, if the value of _C_ is lower.
However, we do not recommend setting _C_ to a very low value like
0.04, since CUBIC with a low _C_ cannot efficiently use the bandwidth
in fast and long-distance networks. Based on these observations and
extensive deployment experience, we find _C_=0.4 gives a good balance
between AIMD- friendliness and aggressiveness of window increase.
Therefore, _C_ SHOULD be set to 0.4. With _C_ set to 0.4, Figure 6
is reduced to:
____
3 / 4
|/ RTT
AVG_W = 1.054 * -------
cubic __
3 / 4
|/ p
Figure 7
Figure 7 is then used in the next subsection to show the scalability
of CUBIC.
5.2. Using Spare Capacity
CUBIC uses a more aggressive window increase function than AIMD TCP
for fast and long-distance networks.
The following table shows that to achieve the 10 Gbps rate, AIMD TCP
requires a packet loss rate of 2.0e-10, while CUBIC requires a packet
loss rate of 2.9e-8.
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+===================+===========+=========+=========+=========+
| Throughput (Mbps) | Average W | AIMD P | HSTCP P | CUBIC P |
+===================+===========+=========+=========+=========+
| 1 | 8.3 | 2.0e-2 | 2.0e-2 | 2.0e-2 |
+-------------------+-----------+---------+---------+---------+
| 10 | 83.3 | 2.0e-4 | 3.9e-4 | 2.9e-4 |
+-------------------+-----------+---------+---------+---------+
| 100 | 833.3 | 2.0e-6 | 2.5e-5 | 1.4e-5 |
+-------------------+-----------+---------+---------+---------+
| 1000 | 8333.3 | 2.0e-8 | 1.5e-6 | 6.3e-7 |
+-------------------+-----------+---------+---------+---------+
| 10000 | 83333.3 | 2.0e-10 | 1.0e-7 | 2.9e-8 |
+-------------------+-----------+---------+---------+---------+
Table 3: Required packet loss rate for AIMD TCP, HSTCP, and
CUBIC to achieve a certain throughput
Table 3 describes the required packet loss rate for AIMD TCP, HSTCP,
and CUBIC to achieve a certain throughput. We use 1500-byte packets
and an _RTT_ of 0.1 seconds.
Our test results in [HKLRX06] indicate that CUBIC uses the spare
bandwidth left unused by existing AIMD TCP flows in the same
bottleneck link without taking away much bandwidth from the existing
flows.
5.3. Difficult Environments
CUBIC is designed to remedy the poor performance of AIMD TCP in fast
and long-distance networks.
5.4. Investigating a Range of Environments
CUBIC has been extensively studied by using both NS-2 simulation and
testbed experiments, covering a wide range of network environments.
More information can be found in [HKLRX06]. Additionally, there is
decade-long deployment experience with CUBIC on the Internet.
Same as AIMD TCP, CUBIC is a loss-based congestion control algorithm.
Because CUBIC is designed to be more aggressive (due to a faster
window increase function and bigger multiplicative decrease factor)
than AIMD TCP in fast and long-distance networks, it can fill large
drop-tail buffers more quickly than AIMD TCP and increases the risk
of a standing queue [RFC8511]. In this case, proper queue sizing and
management [RFC7567] could be used to reduce the packet queuing
delay.
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5.5. Protection against Congestion Collapse
With regard to the potential of causing congestion collapse, CUBIC
behaves like AIMD TCP, since CUBIC modifies only the window
adjustment algorithm of AIMD TCP. Thus, it does not modify the ACK
clocking and timeout behaviors of AIMD TCP.
5.6. Fairness within the Alternative Congestion Control Algorithm
CUBIC ensures convergence of competing CUBIC flows with the same RTT
in the same bottleneck links to an equal throughput. When competing
flows have different RTT values, their throughput ratio is linearly
proportional to the inverse of their RTT ratios. This is true
independently of the level of statistical multiplexing on the link.
5.7. Performance with Misbehaving Nodes and Outside Attackers
This is not considered in the current CUBIC design.
5.8. Behavior for Application-Limited Flows
CUBIC does not increase its congestion window size if a flow is
currently limited by the application instead of the congestion
window. In case of long periods during which _cwnd_ has not been
updated due to such an application limit, such as idle periods, _t_
in Figure 1 MUST NOT include these periods; otherwise, W_(cubic)(_t_)
might be very high after restarting from these periods.
5.9. Responses to Sudden or Transient Events
If there is a sudden congestion, a routing change, or a mobility
event, CUBIC behaves the same as AIMD TCP.
5.10. Incremental Deployment
CUBIC requires only changes to TCP senders, and it does not require
any changes at TCP receivers. That is, a CUBIC sender works
correctly with the AIMD TCP receivers. In addition, CUBIC does not
require any changes to routers and does not require any assistance
from routers.
6. Security Considerations
CUBIC makes no changes to the underlying security of TCP. More
information about TCP security concerns can be found in [RFC5681].
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7. IANA Considerations
This document does not require any IANA actions.
8. References
8.1. 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,
<https://www.rfc-editor.org/rfc/rfc2119>.
[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,
<https://www.rfc-editor.org/rfc/rfc3168>.
[RFC5033] Floyd, S. and M. Allman, "Specifying New Congestion
Control Algorithms", BCP 133, RFC 5033,
DOI 10.17487/RFC5033, August 2007,
<https://www.rfc-editor.org/rfc/rfc5033>.
[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,
<https://www.rfc-editor.org/rfc/rfc5348>.
[RFC5681] Allman, M., Paxson, V., and E. Blanton, "TCP Congestion
Control", RFC 5681, DOI 10.17487/RFC5681, September 2009,
<https://www.rfc-editor.org/rfc/rfc5681>.
[RFC6298] Paxson, V., Allman, M., Chu, J., and M. Sargent,
"Computing TCP's Retransmission Timer", RFC 6298,
DOI 10.17487/RFC6298, June 2011,
<https://www.rfc-editor.org/rfc/rfc6298>.
[RFC6582] Henderson, T., Floyd, S., Gurtov, A., and Y. Nishida, "The
NewReno Modification to TCP's Fast Recovery Algorithm",
RFC 6582, DOI 10.17487/RFC6582, April 2012,
<https://www.rfc-editor.org/rfc/rfc6582>.
[RFC6675] Blanton, E., Allman, M., Wang, L., Jarvinen, I., Kojo, M.,
and Y. Nishida, "A Conservative Loss Recovery Algorithm
Based on Selective Acknowledgment (SACK) for TCP",
RFC 6675, DOI 10.17487/RFC6675, August 2012,
<https://www.rfc-editor.org/rfc/rfc6675>.
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[RFC7567] Baker, F., Ed. and G. Fairhurst, Ed., "IETF
Recommendations Regarding Active Queue Management",
BCP 197, RFC 7567, DOI 10.17487/RFC7567, July 2015,
<https://www.rfc-editor.org/rfc/rfc7567>.
[RFC8174] Leiba, B., "Ambiguity of Uppercase vs Lowercase in RFC
2119 Key Words", BCP 14, RFC 8174, DOI 10.17487/RFC8174,
May 2017, <https://www.rfc-editor.org/rfc/rfc8174>.
8.2. Informative References
[CEHRX07] Cai, H., Eun, D., Ha, S., Rhee, I., and L. Xu, "Stochastic
Ordering for Internet Congestion Control and its
Applications", IEEE INFOCOM 2007 - 26th IEEE International
Conference on Computer Communications,
DOI 10.1109/infcom.2007.111, 2007,
<https://doi.org/10.1109/infcom.2007.111>.
[FHP00] Floyd, S., Handley, M., and J. Padhye, "A Comparison of
Equation-Based and AIMD Congestion Control", May 2000,
<https://www.icir.org/tfrc/aimd.pdf>.
[GV02] Gorinsky, S. and H. Vin, "Extended Analysis of Binary
Adjustment Algorithms", Technical Report TR2002-29,
Department of Computer Sciences, The University of
Texas at Austin, 11 August 2002,
<http://www.cs.utexas.edu/ftp/techreports/tr02-39.ps.gz>.
[HKLRX06] Ha, S., Kim, Y., Le, L., Rhee, I., and L. Xu, "A Step
toward Realistic Performance Evaluation of High-Speed TCP
Variants", International Workshop on Protocols for Fast
Long-Distance Networks, February 2006,
<https://pfld.net/2006/paper/s2_03.pdf>.
[HR08] Ha, S. and I. Rhee, "Hybrid Slow Start for High-Bandwidth
and Long-Distance Networks", International Workshop
on Protocols for Fast Long-Distance Networks, March 2008,
<http://www.hep.man.ac.uk/g/GDARN-IT/pfldnet2008/paper/
Sangate_Ha%20Final.pdf>.
[HRX08] Ha, S., Rhee, I., and L. Xu, "CUBIC: a new TCP-friendly
high-speed TCP variant", ACM SIGOPS Operating Systems
Review Vol. 42, pp. 64-74, DOI 10.1145/1400097.1400105,
July 2008, <https://doi.org/10.1145/1400097.1400105>.
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[K03] Kelly, T., "Scalable TCP: improving performance in
highspeed wide area networks", ACM SIGCOMM Computer
Communication Review Vol. 33, pp. 83-91,
DOI 10.1145/956981.956989, April 2003,
<https://doi.org/10.1145/956981.956989>.
[RFC3522] Ludwig, R. and M. Meyer, "The Eifel Detection Algorithm
for TCP", RFC 3522, DOI 10.17487/RFC3522, April 2003,
<https://www.rfc-editor.org/rfc/rfc3522>.
[RFC3649] Floyd, S., "HighSpeed TCP for Large Congestion Windows",
RFC 3649, DOI 10.17487/RFC3649, December 2003,
<https://www.rfc-editor.org/rfc/rfc3649>.
[RFC3708] Blanton, E. and M. Allman, "Using TCP Duplicate Selective
Acknowledgement (DSACKs) and Stream Control Transmission
Protocol (SCTP) Duplicate Transmission Sequence Numbers
(TSNs) to Detect Spurious Retransmissions", RFC 3708,
DOI 10.17487/RFC3708, February 2004,
<https://www.rfc-editor.org/rfc/rfc3708>.
[RFC3742] Floyd, S., "Limited Slow-Start for TCP with Large
Congestion Windows", RFC 3742, DOI 10.17487/RFC3742, March
2004, <https://www.rfc-editor.org/rfc/rfc3742>.
[RFC4960] Stewart, R., Ed., "Stream Control Transmission Protocol",
RFC 4960, DOI 10.17487/RFC4960, September 2007,
<https://www.rfc-editor.org/rfc/rfc4960>.
[RFC5682] Sarolahti, P., Kojo, M., Yamamoto, K., and M. Hata,
"Forward RTO-Recovery (F-RTO): An Algorithm for Detecting
Spurious Retransmission Timeouts with TCP", RFC 5682,
DOI 10.17487/RFC5682, September 2009,
<https://www.rfc-editor.org/rfc/rfc5682>.
[RFC7661] Fairhurst, G., Sathiaseelan, A., and R. Secchi, "Updating
TCP to Support Rate-Limited Traffic", RFC 7661,
DOI 10.17487/RFC7661, October 2015,
<https://www.rfc-editor.org/rfc/rfc7661>.
[RFC8312] Rhee, I., Xu, L., Ha, S., Zimmermann, A., Eggert, L., and
R. Scheffenegger, "CUBIC for Fast Long-Distance Networks",
RFC 8312, DOI 10.17487/RFC8312, February 2018,
<https://www.rfc-editor.org/rfc/rfc8312>.
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[RFC8511] Khademi, N., Welzl, M., Armitage, G., and G. Fairhurst,
"TCP Alternative Backoff with ECN (ABE)", RFC 8511,
DOI 10.17487/RFC8511, December 2018,
<https://www.rfc-editor.org/rfc/rfc8511>.
[SXEZ19] Sun, W., Xu, L., Elbaum, S., and D. Zhao, "Model-Agnostic
and Efficient Exploration of Numerical State Space of
Real-World TCP Congestion Control Implementations", USENIX
NSDI 2019, February 2019,
<https://www.usenix.org/system/files/nsdi19-sun.pdf>.
[XHR04] Xu, L., Harfoush, K., and I. Rhee, "Binary Increase
Congestion Control (BIC) for Fast Long-Distance Networks",
IEEE INFOCOM 2004, DOI 10.1109/infcom.2004.1354672, March
2004, <https://doi.org/10.1109/infcom.2004.1354672>.
Appendix A. Acknowledgements
Richard Scheffenegger and Alexander Zimmermann originally co-authored
[RFC8312].
Appendix B. Evolution of CUBIC
B.1. Since draft-eggert-tcpm-rfc8312bis-02
* add definition for segments_acked and alpha__(aimd)_. (#47
(https://github.com/NTAP/rfc8312bis/issues/47))
* fix a mistake in _W_(max)_ calculation in the fast convergence
section. (#51 (https://github.com/NTAP/rfc8312bis/issues/51))
* clarity on setting _ssthresh_ and _cwnd_(start)_ during
multiplicative decrease. (#53 (https://github.com/NTAP/rfc8312bis/
issues/53))
B.2. Since draft-eggert-tcpm-rfc8312bis-01
* rename TCP-Friendly to AIMD-Friendly and rename Standard TCP to
AIMD TCP to avoid confusion as CUBIC has been widely used in the
Internet. (#38 (https://github.com/NTAP/rfc8312bis/issues/38))
* change introductory text to reflect the significant broader
deployment of CUBIC in the Internet. (#39
(https://github.com/NTAP/rfc8312bis/issues/39))
* rephrase introduction to avoid referring to variables that have
not been defined yet.
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B.3. Since draft-eggert-tcpm-rfc8312bis-00
* acknowledge former co-authors (#15
(https://github.com/NTAP/rfc8312bis/issues/15))
* prevent _cwnd_ from becoming less than two (#7
(https://github.com/NTAP/rfc8312bis/issues/7))
* add list of variables and constants (#5
(https://github.com/NTAP/rfc8312bis/issues/5), #6
(https://github.com/NTAP/rfc8312bis/issues/6))
* update _K_'s definition and add bounds for CUBIC _target_ _cwnd_
[SXEZ19] (#1 (https://github.com/NTAP/rfc8312bis/issues/1), #14
(https://github.com/NTAP/rfc8312bis/issues/14))
* update _W_(est)_ to use AIMD approach (#20
(https://github.com/NTAP/rfc8312bis/issues/20))
* set alpha__(aimd)_ to 1 once _W_(est)_ reaches _W_(max)_ (#2
(https://github.com/NTAP/rfc8312bis/issues/2))
* add Vidhi as co-author (#17 (https://github.com/NTAP/rfc8312bis/
issues/17))
* note for Fast Recovery during _cwnd_ decrease due to congestion
event (#11 (https://github.com/NTAP/rfc8312bis/issues/11))
* add section for spurious congestion events (#23
(https://github.com/NTAP/rfc8312bis/issues/23))
* initialize _W_(est)_ after timeout and remove variable
_W_(last_max)_ (#28 (https://github.com/NTAP/rfc8312bis/
issues/28))
B.4. Since RFC8312
* converted to Markdown and xml2rfc v3
* updated references (as part of the conversion)
* updated author information
* various formatting changes
* move to Standards Track
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B.5. Since the Original Paper
CUBIC has gone through a few changes since the initial release
[HRX08] of its algorithm and implementation. Below we highlight the
differences between its original paper and [RFC8312].
* The original paper [HRX08] includes the pseudocode of CUBIC
implementation using Linux's pluggable congestion control
framework, which excludes system-specific optimizations. The
simplified pseudocode might be a good source to start with and
understand CUBIC.
* [HRX08] also includes experimental results showing its performance
and fairness.
* The definition of beta__(cubic)_ constant was changed in
[RFC8312]. For example, beta__(cubic)_ in the original paper was
the window decrease constant while [RFC8312] changed it to CUBIC
multiplication decrease factor. With this change, the current
congestion window size after a congestion event in [RFC8312] was
beta__(cubic)_ * _W_(max)_ while it was (1-beta__(cubic)_) *
_W_(max)_ in the original paper.
* Its pseudocode used _W_(last_max)_ while [RFC8312] used _W_(max)_.
* Its AIMD-friendly window was W_(tcp) while [RFC8312] used
_W_(est)_.
Authors' Addresses
Lisong Xu
University of Nebraska-Lincoln
Department of Computer Science and Engineering
Lincoln, NE 68588-0115
United States of America
Email: xu@unl.edu
URI: https://cse.unl.edu/~xu/
Sangtae Ha
University of Colorado at Boulder
Department of Computer Science
Boulder, CO 80309-0430
United States of America
Email: sangtae.ha@colorado.edu
URI: https://netstech.org/sangtaeha/
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Injong Rhee
Bowery Farming
151 W 26TH Street, 12TH Floor
New York, NY 10001
United States of America
Email: injongrhee@gmail.com
Vidhi Goel
Apple Inc.
One Apple Park Way
Cupertino, California 95014
United States of America
Email: vidhi_goel@apple.com
Lars Eggert (editor)
NetApp
Stenbergintie 12 B
FI-02700 Kauniainen
Finland
Email: lars@eggert.org
URI: https://eggert.org/
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