Internet Engineering Task Force (IETF) S. Shalunov
Request for Comments: 6817 G. Hazel
Category: Experimental BitTorrent, Inc.
ISSN: 2070-1721 J. Iyengar
Franklin and Marshall College
M. Kuehlewind
University of Stuttgart
December 2012
Low Extra Delay Background Transport (LEDBAT)
Abstract
Low Extra Delay Background Transport (LEDBAT) is an experimental
delay-based congestion control algorithm that seeks to utilize the
available bandwidth on an end-to-end path while limiting the
consequent increase in queueing delay on that path. LEDBAT uses
changes in one-way delay measurements to limit congestion that the
flow itself induces in the network. LEDBAT is designed for use by
background bulk-transfer applications to be no more aggressive than
standard TCP congestion control (as specified in RFC 5681) and to
yield in the presence of competing flows, thus limiting interference
with the network performance of competing flows.
Status of This Memo
This document is not an Internet Standards Track specification; it is
published for examination, experimental implementation, and
evaluation.
This document defines an Experimental Protocol for the Internet
community. This document is a product of the Internet Engineering
Task Force (IETF). It represents the consensus of the IETF
community. It has received public review and has been approved for
publication by the Internet Engineering Steering Group (IESG). Not
all documents approved by the IESG are a candidate for any level of
Internet Standard; see Section 2 of RFC 5741.
Information about the current status of this document, any errata,
and how to provide feedback on it may be obtained at
http://www.rfc-editor.org/info/rfc6817.
Copyright Notice
Copyright (c) 2012 IETF Trust and the persons identified as the
document authors. All rights reserved.
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Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . 4 ....................................................4
1.1. Requirements Notation . . . . . . . . . . . . . . . . . . 4 ......................................4
1.2. Design Goals . . . . . . . . . . . . . . . . . . . . . . . 4 ...............................................4
1.3. Applicability . . . . . . . . . . . . . . . . . . . . . . 5 ..............................................5
2. LEDBAT Congestion Control . . . . . . . . . . . . . . . . . . 6 .......................................6
2.1. Overview . . . . . . . . . . . . . . . . . . . . . . . . . 6 ...................................................6
2.2. Preliminaries . . . . . . . . . . . . . . . . . . . . . . 6 ..............................................6
2.3. Receiver-Side Operation . . . . . . . . . . . . . . . . . 7 ....................................7
2.4. Sender-Side Operation . . . . . . . . . . . . . . . . . . 7 ......................................7
2.4.1. An Overview . . . . . . . . . . . . . . . . . . . . . 7 .........................................7
2.4.2. The Complete Sender Algorithm . . . . . . . . . . . . 8 .......................8
2.5. Parameter Values . . . . . . . . . . . . . . . . . . . . . 11 ..........................................11
3. Understanding LEDBAT Mechanisms . . . . . . . . . . . . . . . 13 ................................13
3.1. Delay Estimation . . . . . . . . . . . . . . . . . . . . . 13 ..........................................13
3.1.1. Estimating Base Delay . . . . . . . . . . . . . . . . 13 ..............................13
3.1.2. Estimating Queueing Delay . . . . . . . . . . . . . . 13 ..........................13
3.2. Managing the Congestion Window . . . . . . . . . . . . . . 14 ............................14
3.2.1. Window Increase: Probing for More Bandwidth . . . . . 14 ........14
3.2.2. Window Decrease: Responding to Congestion . . . . . . 14 ..........14
3.3. Choosing the Queuing Delay Target . . . . . . . . . . . . 14 .........................15
4. Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . 15 .....................................................15
4.1. Framing and ACK Frequency Considerations . . . . . . . . . 15 ..................15
4.2. Competing with TCP Flows . . . . . . . . . . . . . . . . . 15 ..................................15
4.3. Competing with Non-TCP Flows . . . . . . . . . . . . . . . 16 ..............................16
4.4. Fairness among LEDBAT Flows . . . . . . . . . . . . . . . 16 ...............................16
5. Open Areas for Experimentation . . . . . . . . . . . . . . . . 17 .................................17
5.1. Network Effects and Monitoring . . . . . . . . . . . . . . 17 ............................17
5.2. Parameter Values . . . . . . . . . . . . . . . . . . . . . 18 ..........................................18
5.3. Filters . . . . . . . . . . . . . . . . . . . . . . . . . 18 ...................................................19
5.4. Framing . . . . . . . . . . . . . . . . . . . . . . . . . 19 ...................................................19
6. Security Considerations . . . . . . . . . . . . . . . . . . . 19 ........................................19
7. Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . 19 ...............................................20
8. References . . . . . . . . . . . . . . . . . . . . . . . . . . 20 .....................................................20
8.1. Normative References . . . . . . . . . . . . . . . . . . . 20 ......................................20
8.2. Informative References . . . . . . . . . . . . . . . . . . 20 ....................................20
Appendix A. Measurement Errors . . . . . . . . . . . . . . . . . 21 ....................................21
A.1. Clock Offset . . . . . . . . . . . . . . . . . . . . . . . 21 ...............................................21
A.2. Clock Skew . . . . . . . . . . . . . . . . . . . . . . . . 21 .................................................21
1. Introduction
TCP congestion control [RFC5681] seeks to share bandwidth at a
bottleneck link equitably among flows competing at the bottleneck,
and it is the predominant congestion control mechanism used on the
Internet. However, not all applications seek an equitable share of
network throughput. "Background" applications, such as software
updates or file-sharing applications, seek to operate without
interfering with the performance of more interactive and delay-
and/or bandwidth-sensitive "foreground" applications. Standard TCP
congestion control, as specified in [RFC5681], may be too aggressive
for use with such background applications.
Low Extra Delay Background Transport (LEDBAT) is an experimental
delay-based congestion control mechanism that reacts early to
congestion in the network, thus enabling "background" applications to
use the network while avoiding interference with the network
performance of competing flows. A LEDBAT sender uses one-way delay
measurements to estimate the amount of queueing on the data path,
controls the LEDBAT flow's congestion window based on this estimate,
and minimizes interference with competing flows by adding low extra
queueing delay on the end-to-end path.
Delay-based congestion control protocols, such as TCP-Vegas
[Bra94][Low02], are generally designed to achieve more, not less
throughput than standard TCP, and often outperform TCP under
particular network settings. For further discussion on Lower-than-
Best-Effort transport protocols see [RFC6297]. In contrast, LEDBAT
is designed to be no more aggressive than TCP [RFC5681]; LEDBAT is a
"scavenger" congestion control mechanism that seeks to utilize all
available bandwidth and yields quickly when competing with standard
TCP at a bottleneck link.
In the rest of this document, we refer to congestion control
specified in [RFC5681] as "standard TCP".
1.1. Requirements Notation
The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT",
"SHOULD", "SHOULD NOT", "RECOMMENDED", "MAY", and "OPTIONAL" in this
document are to be interpreted as described in [RFC2119].
1.2. Design Goals
LEDBAT congestion control seeks to achieve the following goals:
1. to utilize end-to-end available bandwidth and to maintain low
queueing delay when no other traffic is present,
2. to add limited queuing delay to that induced by concurrent flows,
and
3. to yield quickly to standard TCP flows that share the same
bottleneck link.
1.3. Applicability
LEDBAT is a "scavenger" congestion control mechanism that is
motivated primarily by background bulk-transfer applications, such as
large file transfers (as with file-sharing applications) and software
updates. It can be used with any application that seeks to minimize
its impact on the network and on other interactive delay- and/or
bandwidth-sensitive network applications. LEDBAT is expected to work
well when the sender and/or receiver is connected via a residential
access network.
LEDBAT can be used as part of a transport protocol or as part of an
application, as long as the data transmission mechanisms are capable
of carrying timestamps and acknowledging data frequently. LEDBAT can
be used with TCP, Stream Control Transmission Protocol (SCTP), and
Datagram Congestion Control Protocol (DCCP), with appropriate
extensions where necessary; and it can be used with proprietary
application protocols, such as those built on top of UDP for peer-to-
peer (P2P) applications.
When used with an ECN-capable framing protocol, LEDBAT should react
to an Explicit Congestion Notification (ECN) mark as it would to a
loss, as specified in [RFC3168].
LEDBAT is designed to reduce buildup of a standing queue by long-
lived LEDBAT flows at a link with a tail-drop FIFO queue, so as to
avoid persistently delaying other flows sharing the queue. If Active
Queue Management (AQM) is configured to drop or ECN-mark packets
before the LEDBAT flow starts reacting to persistent queue buildup,
LEDBAT reverts to standard TCP behavior rather than yielding to other
TCP flows. However, such an AQM is still desirable since it keeps
queuing delay low, achieving an outcome that is in line with LEDBAT's
goals. Additionally, a LEDBAT transport that supports ECN enjoys the
advantages that an ECN-capable TCP enjoys over an ECN-agnostic TCP;
avoiding losses and possible retransmissions. Weighted Fair Queuing
(WFQ), as employed by some home gateways, seeks to isolate and
protect delay-sensitive flows from delays due to standing queues
built up by concurrent long-lived flows. Consequently, while it
prevents LEDBAT from yielding to other TCP flows, it again achieves
an outcome that is in line with LEDBAT's goals [Sch10].
2. LEDBAT Congestion Control
2.1. Overview
A standard TCP sender increases its congestion window until a loss
occurs [RFC5681] or an ECN mark is received [RFC3168], which, in the
absence of link errors in the network, occurs only when the queue at
the bottleneck link on the end-to-end path overflows or an AQM is
applied. Since packet loss or marking at the bottleneck link is
expected to be preceded by an increase in the queueing delay at the
bottleneck link, LEDBAT congestion control uses this increase in
queueing delay as an early signal of congestion, enabling it to
respond to congestion earlier than standard TCP and enabling it to
yield bandwidth to a competing TCP flow.
LEDBAT employs one-way delay measurements to estimate queueing delay.
When the estimated queueing delay is less than a predetermined
target, LEDBAT infers that the network is not yet congested and
increases its sending rate to utilize any spare capacity in the
network. When the estimated queueing delay becomes greater than the
predetermined target, LEDBAT decreases its sending rate as a response
to potential congestion in the network.
2.2. Preliminaries
A LEDBAT sender uses a congestion window (cwnd) to gate the amount of
data that the sender can send into the network in one round-trip time
(RTT). A sender MAY maintain its cwnd in bytes or in packets; this
document uses cwnd in bytes. LEDBAT requires that each data segment
carries a "timestamp" from the sender, based on which the receiver
computes the one-way delay from the sender and sends this computed
value back to the sender.
In addition to the LEDBAT mechanism described below, we note that a
slow start mechanism can be used as specified in [RFC5681]. Since
slow start leads to faster increase in the window than that specified
in LEDBAT, conservative congestion control implementations employing
LEDBAT may skip slow start altogether and start with an initial
window of INIT_CWND * MSS. (INIT_CWND is described later in
Section 2.5.)
The term "MSS", or the sender's Maximum Segment Size, used in this
document refers to the size of the largest segment that the sender
can transmit. The value of MSS can be based on the path MTU
discovery [RFC4821] algorithm and/or on other factors.
2.3. Receiver-Side Operation
A LEDBAT receiver calculates the one-way delay from the sender to the
receiver based on its own system time and timestamps in the received
data packets. The receiver then feeds the computed one-way delay
back to the sender in the next acknowledgement. A LEDBAT receiver
operates as follows:
on data_packet:
remote_timestamp = data_packet.timestamp
acknowledgement.delay = local_timestamp() - remote_timestamp
# fill in other fields of acknowledgement
acknowlegement.send()
acknowledgement.send()
A receiver may choose to delay sending an ACK and may combine
acknowledgements for more than one data packet into a single ACK
packet, as with delayed ACKs in standard TCP, for example. In such
cases, the receiver MAY bundle all the delay samples into one ACK
packet and MUST transmit the samples in the order generated. When
multiple delay samples are bundled within a single ACK, the sender
applies these bundled delay samples at once during its cwnd
adjustment (discussed in the next section). Since the sender's
adjustment may be sensitive to the order in which the delay samples
are applied, the computed delay samples should be available to the
sender in the order they were generated at the receiver.
2.4. Sender-Side Operation
2.4.1. An Overview
As a first approximation, a LEDBAT sender operates as shown below;
the complete algorithm is specified later in Section 2.4.2. TARGET
is the maximum queueing delay that LEDBAT itself may introduce in the
network, and GAIN determines the rate at which the cwnd responds to
changes in queueing delay; both constants are specified later.
off_target is a normalized value representing the difference between
the measured current queueing delay and the predetermined TARGET
delay. off_target can be positive or negative; consequently, cwnd
increases or decreases in proportion to off_target.
on initialization:
base_delay = +INFINITY
on acknowledgement:
current_delay = acknowledgement.delay
base_delay = min(base_delay, current_delay)
queuing_delay = current_delay - base_delay
off_target = (TARGET - queuing_delay) / TARGET
cwnd += GAIN * off_target * bytes_newly_acked * MSS / cwnd
The simplified mechanism above ignores multiple delay samples in an
acknowledgement, noise filtering, base delay expiration, and sender
idle times, which we now take into account in our complete sender
algorithm below.
2.4.2. The Complete Sender Algorithm
update_current_delay() maintains a list of one-way delay
measurements, of which a filtered value is used as an estimate of the
current end-to-end delay. update_base_delay() maintains a list of
one-way delay minima over a number of one-minute intervals, to
measure and to track changes in the base delay of the end-to-end
path. Both of these lists are maintained per LEDBAT flow.
We note this algorithm assumes that slight random fluctuations exist
in inter-packet arrival times at the bottleneck queue, to allow a
LEDBAT sender to correctly measure the base delay. See Section 4.4
for a more complete discussion.
The full sender-side algorithm is given below:
on initialization:
# cwnd is the amount of data that is allowed to be
# outstanding in an RTT and is defined in bytes.
# CTO is the congestion timeout value.
create current_delays list with CURRENT_FILTER elements
create base_delays list with BASE_HISTORY number of elements
initialize elements in base_delays to +INFINITY
initialize elements in current_delays according to FILTER()
last_rollover = -INFINITY # More than a minute in the past
flightsize = 0
cwnd = INIT_CWND * MSS
CTO = 1 second
on acknowledgement:
# flightsize is the amount of data outstanding before this ACK
# was received and is updated later;
# bytes_newly_acked is the number of bytes that this ACK
# newly acknowledges, and it MAY be set to MSS.
for each delay sample in the acknowledgement:
delay = acknowledgement.delay
update_base_delay(delay)
update_current_delay(delay)
queuing_delay = FILTER(current_delays) - MIN(base_delays)
off_target = (TARGET - queuing_delay) / TARGET
cwnd += GAIN * off_target * bytes_newly_acked * MSS / cwnd
max_allowed_cwnd = flightsize + ALLOWED_INCREASE * MSS
cwnd = min(cwnd, max_allowed_cwnd)
cwnd = max(cwnd, MIN_CWND * MSS)
flightsize = flightsize - bytes_newly_acked
update_CTO()
on data loss:
# at most once per RTT
cwnd = min (cwnd, max (cwnd/2, MIN_CWND * MSS))
if data lost is not to be retransmitted:
flightsize = flightsize - bytes_not_to_be_retransmitted
if no ACKs are received within a CTO:
# extreme congestion, or significant RTT change.
# set cwnd to 1MSS and backoff the congestion timer.
cwnd = 1 * MSS
CTO = 2 * CTO
update_CTO()
# implements an RTT estimation mechanism using data
# transmission times and ACK reception times,
# which is used to implement a congestion timeout (CTO).
# If implementing LEDBAT in TCP, sender SHOULD use
# mechanisms described in RFC 6298 [RFC6298],
# and the CTO would be the same as the retransmission timeout (RTO).
update_current_delay(delay)
# Maintain a list of CURRENT_FILTER last delays observed.
delete first item in current_delays list
append delay to current_delays list
update_base_delay(delay)
# Maintain BASE_HISTORY delay-minima.
# Each minimum is measured over a period of a minute.
# 'now' is the current system time
if round_to_minute(now) != round_to_minute(last_rollover)
last_rollover = now
delete first item in base_delays list
append delay to base_delays list
else
base_delays.tail = MIN(base_delays.tail, delay)
The LEDBAT sender seeks to extract the actual delay estimate from the
current_delay samples by implementing FILTER() to eliminate any
outliers. Different types of filters MAY be used for FILTER() -- a
NULL filter, that does not filter at all, is a reasonable candidate
as well, since LEDBAT's use of a linear controller for cwnd increase
and decrease may allow it to recover quickly from errors induced by
bad samples. Another example of a filter is the exponentially
weighted moving average (EWMA) function, with weights that enable
agile tracking of changing network delay. A simple MIN filter
applied over a small window (much smaller than BASE_HISTORY) may also
provide robustness to large delay peaks, as may occur with delayed
ACKs in TCP. Care should be taken that the filter used, while
providing robustness to noise, remains sensitive to persistent
congestion signals.
We note that when multiple delay samples are bundled within a single
ACK, the sender's resulting cwnd may be slightly different than when
the samples are sent individually in separate ACKs. The cwnd is
adjusted based on the total number of bytes ACKed and the final
filtered value of queueing_delay, irrespective of the number of delay
samples in an ACK.
To implement an approximate minimum over the past few minutes, a
LEDBAT sender stores BASE_HISTORY separate minima -- one each for the
last BASE_HISTORY-1 minutes, and one for the running current minute.
At the end of the current minute, the window moves -- the earliest
minimum is dropped and the latest minimum is added. If the
connection is idle for a given minute, no data is available for the
one-way delay and, therefore, a value of +INFINITY has to be stored
in the list. If the connection has been idle for BASE_HISTORY
minutes, all minima in the list are thus set to +INFINITY and
measurement begins anew. LEDBAT thus requires that during idle
periods, an implementation must maintain the base delay list.
LEDBAT restricts cwnd growth after a period of inactivity. When the
sender is application-limited, the sender's cwnd is clamped down
using max_allowed_cwnd to a little more than flightsize. To be TCP-
friendly, LEDBAT halves its cwnd on data loss.
LEDBAT uses a congestion timeout (CTO) to avoid transmitting data
during periods of heavy congestion and to avoid congestion collapse.
A CTO is used to detect heavy congestion indicated by loss of all
outstanding data or acknowledgements, resulting in reduction of the
cwnd to 1 MSS and an exponential backoff of the CTO interval. This
backoff of the CTO value avoids sending more data into an overloaded
queue, and it also allows the sender to cope with sudden changes in
the RTT of the path. The function of a CTO is similar to that of an
retransmission timeout (RTO) in TCP [RFC6298], but since LEDBAT
separates reliability from congestion control, a retransmission need
not be triggered by a CTO. LEDBAT, however, does not preclude a CTO
from triggering retransmissions, as could be the case if LEDBAT
congestion control were to be used with TCP framing and reliability.
The CTO is a gating mechanism that ensures exponential backoff of
sending rate under heavy congestion, and it may be implemented with
or without a timer. An implementation choosing to avoid timers may
consider using a "next-time-to-send" variable, set based on the CTO,
to control the earliest time a sender may transmit without receiving
any ACKs. A maximum value MAY be placed on the CTO, and if placed,
it MUST be at least 60 seconds.
2.5. Parameter Values
TARGET MUST be 100 milliseconds or less, and this choice of value is
explained further in Section 3.3. Note that using the same TARGET
value across LEDBAT flows enables equitable sharing of the bottleneck
bandwidth. A flow with a higher TARGET value than other competing
LEDBAT flows may get a larger share of the bottleneck bandwidth. It
is possible to consider the use of different TARGET values for
implementing a relative priority between two competing LEDBAT flows
by setting a higher TARGET value for the higher-priority flow.
ALLOWED_INCREASE SHOULD be 1, and it MUST be greater than 0. An
ALLOWED_INCREASE of 0 results in no cwnd growth at all, and an
ALLOWED_INCREASE of 1 allows and limits the cwnd increase based on
flightsize in the previous RTT. An ALLOWED_INCREASE greater than 1
MAY be used when interactions between LEDBAT and the framing protocol
provide a clear reason for doing so.
GAIN MUST be set to 1 or less. A GAIN of 1 limits the maximum cwnd
ramp-up to the same rate as TCP Reno in Congestion Avoidance. While
this document specifies the use of the same GAIN for both cwnd
increase (when off_target is greater than zero) and decrease (when
off_target is less than zero), implementations MAY use a higher GAIN
for cwnd decrease than for the increase; our justification follows.
When a competing non-LEDBAT flow increases its sending rate, the
LEDBAT sender may only measure a small amount of additional delay and
decrease the sending rate slowly. To ensure no impact on a competing
non-LEDBAT flow, the LEDBAT flow should decrease its sending rate at
least as quickly as the competing flow increases its sending rate. A
higher decrease-GAIN MAY be used to allow the LEDBAT flow to decrease
its sending rate faster than the competing flow's increase rate.
The size of the base_delays list, BASE_HISTORY, SHOULD be 10. If the
actual base delay decreases, due to a route change, for instance, a
LEDBAT sender adapts immediately, irrespective of the value of
BASE_HISTORY. If the actual base delay increases, however, a LEDBAT
sender will take BASE_HISTORY minutes to adapt and may wrongly infer
a little more extra delay than intended (TARGET) in the meanwhile. A
value for BASE_HISTORY is thus a trade-off: a higher value may yield
a more accurate measurement when the base delay is unchanging, and a
lower value results in a quicker response to actual increase in base
delay.
A LEDBAT sender uses the current_delays list to maintain only delay
measurements made within an RTT amount of time in the past, seeking
to eliminate noise spikes in its measurement of the current one-way
delay through the network. The size of this list, CURRENT_FILTER,
may be variable, and it depends on the FILTER() function as well as
the number of successful measurements made within an RTT amount of
time in the past. The sender should seek to gather enough delay
samples in each RTT so as to have statistical confidence in the
measurements. While the number of delay samples required for such
confidence will vary depending on network conditions, the sender
SHOULD use at least 4 delay samples in each RTT, unless the number of
samples is lower due to a small congestion window. The value of
CURRENT_FILTER will depend on the filter being employed, but
CURRENT_FILTER MUST be limited such that samples in the list are not
older than an RTT in the past.
INIT_CWND and MIN_CWND SHOULD both be 2. An INIT_CWND of 2 should
help seed FILTER() at the sender when there are no samples at the
beginning of a flow, and a MIN_CWND of 2 allows FILTER() to use more
than a single instantaneous delay estimate while not being too
aggressive. Slight deviations may be warranted, for example, when
these values of INIT_CWND and MIN_CWND interact poorly with the
framing protocol. However, INIT_CWND and MIN_CWND MUST be no larger
than the corresponding values specified for TCP [RFC5681].
3. Understanding LEDBAT Mechanisms
This section describes the delay estimation and window management
mechanisms used in LEDBAT.
3.1. Delay Estimation
LEDBAT estimates congestion in the direction of the data flow, and to
avoid measuring additional delay from, e.g., queue buildup on the
reverse path (or ACK path) or reordering, LEDBAT uses one-way delay
estimates. LEDBAT assumes that measurements are done with data
packets, thus avoiding the need for separate measurement packets and
avoiding the pitfall of measurement packets being treated differently
from the data packets in the network.
End-to-end delay can be decomposed into transmission (or
serialization) delay, propagation (or speed-of-light) delay, queueing
delay, and processing delay. On any given path, barring some noise,
all delay components except for queueing delay are constant. To
observe an increase in the queueing delay in the network, a LEDBAT
sender separates the queueing delay component from the rest of the
end-to-end delay, as described below.
3.1.1. Estimating Base Delay
Since queuing delay is always additive to the end-to-end delay,
LEDBAT estimates the sum of the constant delay components, which we
call "base delay", to be the minimum delay observed on the end-to-end
path.
To respond to true changes in the base delay, as can be caused by a
route change, LEDBAT uses only recent measurements in estimating the
base delay. The duration of the observation window itself is a
trade-off between robustness of measurement and responsiveness to
change -- a larger observation window increases the chances that the
true base delay will be detected (as long as the true base delay is
unchanged), whereas a smaller observation window results in faster
response to true changes in the base delay.
3.1.2. Estimating Queueing Delay
Assuming that the base delay is constant (in the absence of any route
changes), the queueing delay is represented by the variable component
of the measured end-to-end delay. LEDBAT measures queueing delay as
simply the difference between an end-to-end delay measurement and the
current estimate of base delay. The queueing delay should be
filtered (depending on the usage scenario) to eliminate noise in the
delay estimation, such as due to spikes in processing delay at a node
on the path.
3.2. Managing the Congestion Window
LEDBAT uses a simple linear controller to determine the sending rate
as a function of the delay estimate, where the response of the sender
is proportional to the difference between the current queueing delay
estimate and the target.
3.2.1. Window Increase: Probing for More Bandwidth
When the queuing delay is smaller than a delay target value, as
specified by the TARGET parameter in this document, a LEDBAT sender
will increase its congestion window proportionally to the relative
difference between the current queueing delay and the delay target.
As the current queuing delay gets closer to TARGET, LEDBAT's window
growth gets slower. To compete fairly with concurrent TCP flows, we
set the highest rate of LEDBAT's window growth (when the current
queueing delay estimate is zero) to be the same as TCP's (increase of
one packet per RTT). In other words, a LEDBAT flow never ramps up
faster than a competing TCP flow over the same path. The TARGET
value specifies the maximum extra queuing delay that LEDBAT will
induce. If the current queuing delay equals the TARGET value, LEDBAT
tries to maintain this extra delay.
3.2.2. Window Decrease: Responding to Congestion
When a sender's queueing delay estimate is higher than the target,
the LEDBAT flow's rate should be reduced. LEDBAT's linear controller
allows the sender to decrease the window proportional to the
difference between the target and the current queueing delay.
Unlike TCP-like loss-based congestion control, LEDBAT seeks to avoid
losses and so a LEDBAT sender is not expected to normally rely on
losses to determine the sending rate. However, when data loss does
occur, LEDBAT must respond as standard TCP does; even if the queueing
delay estimates indicate otherwise, a loss is assumed to be a strong
indication of congestion. Thus, to deal with severe congestion when
packets are dropped in the network, and to provide a fallback against
incorrect queuing delay estimates, a LEDBAT sender halves its
congestion window when a loss event is detected. As with TCP New-
Reno, LEDBAT reduces its cwnd by half at most once per RTT.
3.3. Choosing the Queuing Delay Target
The International Telecommunication Union's (ITU's) Recommendation
G.114 defines a one-way delay of 150 ms to be acceptable for most
user voice applications [g114]. Thus, the delay induced by LEDBAT
must be well below 150 ms to limit its impact on concurrent delay-
sensitive traffic sharing the same bottleneck queue. A target that
is too low, on the other hand, increases the sensitivity of the
sender's algorithm to noise in the one-way delays and in the delay
measurement process, and may lead to reduced throughput for the
LEDBAT flow and to under-utilization of the bottleneck link.
Our recommendation of 100 ms or less as the target is a trade-off
between these considerations. Anecdotal evidence indicates that this
value works well -- LEDBAT has been implemented and successfully
deployed with a target value of 100 ms in two BitTorrent
implementations: as the exclusive congestion control mechanism in
BitTorrent Delivery Network Accelerator (DNA), and as an experimental
mechanism in uTorrent [uTorrent].
4. Discussion
4.1. Framing and ACK Frequency Considerations
While the actual framing and wire format of the protocols using
LEDBAT are outside the scope of this document, we briefly consider
the data framing and ACK frequency needs of LEDBAT mechanisms.
To compute the data path's one-way delay, our discussion of LEDBAT
assumes a framing that allows the sender to timestamp packets and for
the receiver to convey the measured one-way delay back to the sender
in ACK packets. LEDBAT does not require this particular method, but
it does require unambiguous delay estimates using data and ACK
packets.
A LEDBAT receiver may send an ACK as frequently as one for every data
packet received or less frequently; LEDBAT does require that the
receiver MUST transmit at least one ACK in every RTT.
4.2. Competing with TCP Flows
LEDBAT is designed to respond to congestion indications earlier than
loss-based standard TCP [RFC5681]. A LEDBAT flow gets more
aggressive as the queueing delay estimate gets lower; since the
queueing delay estimate is non-negative, LEDBAT is most aggressive
when the queueing delay estimate is zero. In this case, LEDBAT ramps
up its congestion window at the same rate as standard TCP [RFC5681].
LEDBAT may reduce its rate earlier than standard TCP and always
halves its congestion window on loss. Thus, in the worst case, where
the delay estimates are completely and consistently off, a LEDBAT
flow falls back to standard TCP behavior, and is no more aggressive
than standard TCP [RFC5681].
4.3. Competing with Non-TCP Flows
While LEDBAT yields to all high-load flows, both TCP and non-TCP,
LEDBAT may not yield to low-load and latency-sensitive traffic that
do not induce a measurable delay at the bottleneck queue, such as
Voice over IP (VoIP) traffic. While such flows will experience
additional delay due to any concurrent LEDBAT flows, the TARGET delay
sets a limit to the total amount of additional delay that all the
concurrent LEDBAT flows will jointly induce. If the TARGET delay is
higher than what the bottleneck queue can sustain, the LEDBAT flows
should experience loss and will fall back to standard loss-based TCP
behavior. Thus, in the worst case, LEDBAT will add no more latency
than standard TCP when competing with non-TCP flows. In the common
case however, we expect LEDBAT flows to add TARGET amount of delay,
which ought to be within the delay tolerance for most latency-
sensitive applications, including VoIP applications.
4.4. Fairness among LEDBAT Flows
The primary design goals of LEDBAT are focused on the aggregate
behavior of LEDBAT flows when they compete with standard TCP. Since
LEDBAT is designed for background traffic, we consider link
utilization to be more important than fairness amongst LEDBAT flows.
Nevertheless, we now consider fairness issues that might arise
amongst competing LEDBAT flows.
LEDBAT as described so far lacks a mechanism specifically designed to
equalize utilization amongst LEDBAT flows. Anecdotally observed
behavior of existing implementations indicates that a rough
equalization does occur since in most enviroments environments some amount of
randomness in the inter-packet transmission times exists, as
explained further below.
Delay-based congestion control systems suffer from the possibility of
latecomers incorrectly measuring and using a higher base-delay than
an active flow that started earlier. Consider that a bottleneck is
saturated by a single LEDBAT flow, and the flow therefore maintains
the bottleneck queue at TARGET delay. When a new LEDBAT flow arrives
at the bottleneck, it might incorrectly include the steady queueing
delay in its measurement of the base delay on the path. The new flow
has an inflated estimate of the base delay, and may now effectively
build on top of the existing, already maximal, queueing delay. As
the latecomer flow builds up, the old flow sees the true queueing
delay and backs off, while the latecomer keeps building up, using up
the entire link's capacity, and effectively shutting the old flow
out. This advantage is called the "latecomer's advantage".
In the worst case, if the first flow yields at the same rate as the
new flow increases its sending rate, the new flow will see constant
end-to-end delay, which it assumes is the base delay, until the first
flow backs off completely. As a result, by the time the second flow
stops increasing its cwnd, it would have added twice the target
queueing delay to the network.
This advantage can be reduced if the first flow yields and empties
the bottleneck queue faster than the incoming flow increases its
occupancy in the queue. In such a case, the latecomer might measure
correctly a delay that is closer to the base delay. While such a
reduction might be achieved through a multiplicative decrease of the
congestion window, this may cause strong fluctuations in flow
throughput during the flow's steady state. Thus, we do not recommend
a multiplicative decrease scheme.
We note that in certain use-case scenarios, it is possible for a
later LEDBAT flow to gain an unfair advantage over an existing one
[Car10]. In practice, this concern ought to be alleviated by the
burstiness of network traffic: all that's needed to measure the base
delay is one small gap in transmission schedules between the LEDBAT
flows. These gaps can occur for a number of reasons such as latency
introduced due to application sending patterns, OS scheduling at the
sender, processing delay at the sender or any network node, and link
contention. When such a gap occurs in the first sender's
transmission while the latecomer is starting, base delay is
immediately correctly measured. With a small number of LEDBAT flows,
system noise may sufficiently regulate the latecomer's advantage.
5. Open Areas for Experimentation
We now outline some areas that need experimentation in the Internet
and under different network scenarios. These experiments should help
the community understand LEDBAT's dynamics and should help towards
further standardization of LEDBAT and LEDBAT-related documents.
5.1. Network Effects and Monitoring
Further study is required to fully understand the behavior and
convergence properties of LEDBAT in networks with non-tail-drop, non-
FIFO queues, in networks with frequent route changes, and in networks
with network-level load balancing. These studies should have two
broad goals: (i) to understand the effects of different network
mechanisms on LEDBAT, and (ii) to understand the impact of LEDBAT on
the network.
Network mechanisms and dynamics can influence LEDBAT flows in
unintended ways. For instance, frequent route changes that result in
increasing base delays may, in the worst case, throttle a LEDBAT
flow's throughput significantly. The influence of different network
traffic management mechanisms on LEDBAT throughput should be studied.
An increasing number of LEDBAT flows in the network will likely
result in operator-visible network effects as well, and these should
thus be studied. For instance, as long as the bottleneck queue in a
network is larger than TARGET (in terms of delay), we expect that
both the average queueing delay and loss rate in the network should
reduce as LEDBAT traffic increasingly dominates the traffic mix in
the network. Note that for bottleneck queues that are smaller than
TARGET, LEDBAT will appear to behave very similar to standard TCP and
its flow-level behavior may not be distinguishable from that of
standard TCP.
We note that a network operator may be able to verify the operation
of a LEDBAT flow by monitoring per-flow behavior and queues in the
network -- when the queueing delay at a bottleneck queue is above
TARGET as specified in this document, LEDBAT flows should be expected
to back off and reduce their sending rate.
5.2. Parameter Values
The throughput and response of LEDBAT to the proposed parameter
values of TARGET, decrease-GAIN, BASE_HISTORY, INIT_CWND, and
MIN_CWND should be evaluated with different types of competing
traffic in different network settings, including with different AQM
schemes at the bottleneck queue. TARGET controls LEDBAT's added
latency, while decrease-GAIN controls LEDBAT's response to competing
traffic. Since LEDBAT is intended to be minimally intrusive to
competing traffic, the impact of TARGET and decrease-GAIN on delay-
sensitive traffic should be studied. TARGET also impacts the growth
rate of the congestion window when off_target is smaller than 1.
This impact of TARGET on the rate of cwnd growth should be studied.
The amount of history maintained by the base delay estimator,
BASE_HISTORY, influences the responsiveness of LEDBAT to changing
network conditions. LEDBAT's responsiveness and throughput should be
evaluated in the wide area and under conditions where abrupt changes
in base delay might occur, such as with route changes and with
cellular handovers. The impact and efficacy of these parameters
should be carefully studied with tests over the Internet.
5.3. Filters
LEDBAT's effectiveness depends on a sender's ability to accurately
estimate end-to-end queueing delay from delay samples. Consequently,
the filtering algorithm used for this estimation, FILTER(), is an
important candidate for experiments. This document suggests the use
of NULL, EWMA, and MIN filters for estimating the current delay; the
efficacy of these and other possible filters for this estimate should
be investigated. FILTER() may also impact cwnd dynamics when delay
samples are bundled in ACKs, since cwnd adaption is done once per ACK
irrespective of the number of delay samples in the ACK. This impact
should be studied when the different filters are considered.
5.4. Framing
This document defines only a congestion control algorithm and assumes
that framing mechanisms for exchanging delay information exist within
the protocol in which LEDBAT is being implemented. If implemented in
a new protocol, both the sender and receiver may be LEDBAT-aware, but
if implemented in an existing protocol that is capable of providing
one-way delay information, LEDBAT may be implemented as a sender-
side-only modification. In either case, the parent protocol may
interact with LEDBAT's algorithms; for instance, the rate of ACK
feedback to the data sender may be dictated by other protocol
parameters, but will interact with the LEDBAT flow's dynamics.
Careful experimentation is necessary to understand and integrate
LEDBAT into both new and existing protocols.
6. Security Considerations
LEDBAT's aggressiveness is contingent on the delay estimates and on
the TARGET delay value. If these parameter values at the sender are
compromised such that delay estimates are artificially set to zero
and the TARGET delay value is set to +INFINITY, the LEDBAT algorithm
deteriorates to TCP-like behavior. Thus, while LEDBAT is sensitive
to these parameters, the algorithm is fundamentally limited in the
worst case to be as aggressive as standard TCP.
A man in the middle may be able to change queueing delay on a network
path, and/or modify the timestamps transmitted by a LEDBAT sender
and/or modify the delays reported by a LEDBAT receiver, thus causing
a LEDBAT flow to back off even when there's no congestion. A
protocol using LEDBAT ought to minimize the risk of such man-in-the-
middle attacks by at least authenticating the timestamp field in the
data packets and the delay field in the ACK packets.
LEDBAT is not known to introduce any new concerns with privacy,
integrity, or other security issues for flows that use it. LEDBAT is
compatible with use of IPsec and Transport Layer Security (TLS) /
Datagram Transport Layer Security (DTLS).
7. Acknowledgements
We thank folks in the LEDBAT working group for their comments and
feedback. Special thanks to Murari Sridharan and Rolf Winter for
their patient and untiring shepherding.
8. References
8.1. 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.
[RFC4821] Mathis, M. and J. Heffner, "Packetization Layer Path MTU
Discovery", RFC 4821, March 2007.
[RFC5681] Allman, M., Paxson, V., and E. Blanton, "TCP Congestion
Control", RFC 5681, September 2009.
[RFC6298] Paxson, V., Allman, M., Chu, J., and M. Sargent,
"Computing TCP's Retransmission Timer", RFC 6298,
June 2011.
8.2. Informative References
[Bra94] Brakmo, L., O'Malley, S., and L. Peterson, "TCP Vegas:
New techniques for congestion detection and avoidance",
Proceedings of SIGCOMM '94, pages 24-35, August 1994.
[Car10] Carofiglio, G., Muscariello, L., Rossi, D., Testa, C.,
and S. Valenti, "Rethinking Low Extra Delay Background
Transport Protocols", arXiv:1010.5623v1, September 2010. October 2010,
<http://arxiv.org/abs/1010.5623v1>.
[Low02] Low, S., Peterson, L., and L. Wang, "Understanding TCP
Vegas: A Duality Model", JACM 49 (2), March 2002.
[RFC5905] Mills, D., Martin, J., Burbank, J., and W. Kasch,
"Network Time Protocol Version 4: Protocol and Algorithms
Specification", RFC 5905, June 2010.
[RFC6297] Welzl, M. and D. Ros, "A Survey of Lower-than-Best-Effort
Transport Protocols", RFC 6297, June 2011.
[Sch10] Schneider, J., Wagner, J., Winter, R., and H. Kolbe, "Out
of my Way -- Evaluating Low Extra Delay Background
Transport in an ADSL Access Network", Proceedings of 22nd
International Teletraffic Congress (ITC22), September
2010.
[g114] "SERIES G: TRANSMISSION SYSTEMS AND MEDIA, DIGITAL
SYSTEMS AND NETWORKS; International telephone connections
and circuits - General; Recommendations on the
transmission quality for an entire international
telephone connection; One-way transmission time", ITU-T
Recommendation G.114, 05/2003.
[uTorrent] Hazel, G., "uTorrent Transport Protocol library",
http://github.com/bittorrent/libutp,
July 2012. 2012, <http://github.com/bittorrent/libutp>.
Appendix A. Measurement Errors
LEDBAT measures and uses one-way delays, and we now consider
measurement errors in timestamp generation and use. In this section,
we use the same locally linear clock model and the same terminology
as Network Time Protocol (NTP) [RFC5905]. In particular, NTP uses
the terms "offset" to refer to the difference between measured time
and true time, and "skew" to refer to difference of clock rate from
the true rate. A clock thus has two time measurement errors: a fixed
offset from the true time, and a skew. We now consider these errors
in the context of LEDBAT.
A.1. Clock Offset
The offset of the clocks, both the sender's and the receiver's, shows
up as a fixed error in LEDBAT's one-way delay measurement. The
offset in the measured one-way delay is simply the difference in
offsets between the receiver's and the sender's clocks. LEDBAT,
however, does not use this estimate directly, but uses the difference
between the measured one-way delay and a measured base delay. Since
the offset error (difference of clock offsets) is the same for the
measured one-way delay and the base delay, the offsets cancel each
other out in the queuing delay estimate, which LEDBAT uses for its
window computations. Clock offset error thus has no impact on
LEDBAT.
A.2. Clock Skew
Clock skew generally shows up as a linearly changing error in a time
estimate. Similar to the offset, the skew of LEDBAT's one-way delay
estimate is thus the difference between the two clocks' skews.
Unlike the offset, however, skew does not cancel out when the queuing
delay estimate is computed, since it causes the two clocks' offsets
to change over time.
While the offset could be large, with some clocks off by minutes or
even hours or more, skew is typically small. Typical skews of
untrained clocks seem to be around 100-200 parts per million (ppm)
[RFC5905], where a skew of 100 ppm translates to an error
accumulation of 6 milliseconds per minute. This accumulation is
limited in LEDBAT, since any error accumulation is limited to the
amount of history maintained by the base delay estimator, as dictated
by the BASE_HISTORY parameter. The effects of clock skew error on
LEDBAT should generally be insignificant unless the skew is unusually
high, or unless extreme values have been chosen for TARGET (extremely
low) and BASE_HISTORY (extremely large). Nevertheless, we now
consider the possible impact of skew on LEDBAT behavior.
Clock skew can manifest in two ways: the sender's clock can be faster
than the receiver's clock, or the receiver's clock can be faster than
the sender's clock. In the first case, the measured one-way delay
will decrease as the sender's clock drifts forward. While this drift
can lead to an artificially low estimate of the queueing delay, the
drift should also lead to a lower base delay measurement, which
consequently absorbs the erroneous reduction in the one-way delay
estimates.
In the second case, the one-way delay estimate will artificially
increase with time. This increase can reduce a LEDBAT flow's
throughput unnecessarily. In this case, a skew correction mechanism
can be beneficial.
We now discuss an example clock skew correction mechanism. In this
example, the receiver sends back raw (sending and receiving)
timestamps. Using this information, the sender can estimate one-way
delays in both directions, and the sender can also compute and
maintain an estimate of the base delay as would be observed by the
receiver. If the sender detects the receiver reducing its estimate
of the base delay, it may infer that this reduction is due to clock
drift. The sender then compensates by increasing its base delay
estimate by the same amount. To apply this mechanism, timestamps
need to be transmitted in both directions.
We now outline a few other ideas that can be used for skew
correction.
o Skew correction with faster virtual clock:
Since having a faster clock on the sender will result in
continuous updates of the base delay, a faster virtual clock can
be used for sender timestamping. This virtual clock can be
computed from the default machine clock through a linear
transformation. For instance, with a 500 ppm speed-up the
sender's clock is very likely to be faster than a receiver's
clock. Consequently, LEDBAT will benefit from the implicit
correction when updating the base delay.
o Skew correction with estimating drift:
A LEDBAT sender maintains a history of base delay minima. This
history can provide a base to compute the clock skew difference
between the two hosts. The slope of a linear function fitted to
the set of minima base delays gives an estimate of the clock skew.
This estimation can be used to correct the clocks. If the other
endpoint is doing the same, the clock should be corrected by half
of the estimated skew amount.
o Byzantine skew correction:
When it is known that each host maintains long-lived connections
to a number of different other hosts, a byzantine scheme can be
used to estimate the skew with respect to the true time. Namely,
a host calculates the skew difference for each of the peer hosts
as described with the previous approach, then take the median of
the skew differences. While this scheme is not universally
applicable, it combines well with other schemes, since it is
essentially a clock training mechanism. The scheme also corrects
fast, since state is preserved between connections.
Authors' Addresses
Stanislav Shalunov
BitTorrent, Inc.
303 Second St., Suite S200
San Francisco, CA 94107
USA
EMail: shalunov@shlang.com
URI: http://shlang.com
Greg Hazel
BitTorrent, Inc.
303 Second St., Suite S200
San Francisco, CA 94107
USA
EMail: greg@bittorrent.com
Janardhan Iyengar
Franklin and Marshall College
415 Harrisburg Ave.
Lancaster, PA 17603
USA
EMail: jiyengar@fandm.edu
Mirja Kuehlewind
University of Stuttgart
Stuttgart
DE
EMail: mirja.kuehlewind@ikr.uni-stuttgart.de