LEDBAT WG S. Shalunov
Internet-Draft G. Hazel
Intended status: Experimental BitTorrent Inc
Expires: November 11, 2011 J. Iyengar
Franklin and Marshall College
M. Kuehlewind
University of Stuttgart
May 10, 2011
Low Extra Delay Background Transport (LEDBAT)
draft-ietf-ledbat-congestion-05.txt
Abstract
LEDBAT is an experimental delay-based congestion control algorithm
that attempts to utilize the available bandwidth on an end-to-end
path while limiting the consequent increase in queueing delay on the
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; it is
designed to be no more aggressive than TCP congestion control and to
yield in the presence of any competing TCP flows, thus limiting
interference with the network performance of the competing flows.
Status of this Memo
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This Internet-Draft will expire on November 11, 2011.
Copyright Notice
Copyright (c) 2011 IETF Trust and the persons identified as the
document authors. All rights reserved.
This document is subject to BCP 78 and the IETF Trust's Legal
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Table of Contents
1. Requirements notation . . . . . . . . . . . . . . . . . . . . 3
2. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . 3
2.1. Design Goals . . . . . . . . . . . . . . . . . . . . . . . 3
2.2. Applicability . . . . . . . . . . . . . . . . . . . . . . 4
3. LEDBAT Congestion Control . . . . . . . . . . . . . . . . . . 4
3.1. Overview . . . . . . . . . . . . . . . . . . . . . . . . . 4
3.2. Preliminaries . . . . . . . . . . . . . . . . . . . . . . 5
3.3. Receiver-Side Operation . . . . . . . . . . . . . . . . . 5
3.4. Sender-Side Operation . . . . . . . . . . . . . . . . . . 5
3.4.1. An Overview . . . . . . . . . . . . . . . . . . . . . 5
3.4.2. The Complete Sender Algorithm . . . . . . . . . . . . 6
3.5. Parameter Values . . . . . . . . . . . . . . . . . . . . . 8
4. Understanding LEDBAT Mechanisms . . . . . . . . . . . . . . . 9
4.1. Delay Estimation . . . . . . . . . . . . . . . . . . . . . 9
4.1.1. Estimating Base Delay . . . . . . . . . . . . . . . . 10
4.1.2. Estimating Queueing Delay . . . . . . . . . . . . . . 10
4.2. Managing the Congestion Window . . . . . . . . . . . . . . 10
4.2.1. Window Increase: Probing For More Bandwidth . . . . . 10
4.2.2. Window Decrease: Responding To Congestion . . . . . . 10
4.3. Choosing The Queuing Delay Target . . . . . . . . . . . . 11
5. Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . 11
5.1. Framing and Ack Frequency Considerations . . . . . . . . . 11
5.2. Competing With TCP Flows . . . . . . . . . . . . . . . . . 12
5.3. Fairness Among LEDBAT Flows . . . . . . . . . . . . . . . 12
6. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 13
7. Security Considerations . . . . . . . . . . . . . . . . . . . 13
8. Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . 13
9. References . . . . . . . . . . . . . . . . . . . . . . . . . . 14
9.1. Normative References . . . . . . . . . . . . . . . . . . . 14
9.2. Informative References . . . . . . . . . . . . . . . . . . 14
Appendix A. Timestamp errors . . . . . . . . . . . . . . . . . . 14
A.1. Clock offset . . . . . . . . . . . . . . . . . . . . . . . 14
A.2. Clock skew . . . . . . . . . . . . . . . . . . . . . . . . 14
A.3. Clock skew correction mechanism . . . . . . . . . . . . . 15
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . . 16
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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].
2. 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. Not all applications seek an equitable share of network
throughput, however---"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---and standard
TCP may be too aggressive for use with such background applications.
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 avoidoing
interference with the network performance of competing TCP 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 TCP flows by adding low extra queueing delay on the end-to-
end path.
Delay-based congestion control protocols, such as TCP-Vegas [Bra94],
are generally designed to achieve more, not less throughput than
standard TCP, and often outperform TCP under particular network
settings. In contrast, LEDBAT is designed to be no more aggressive
than TCP; 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.
2.1. Design Goals
LEDBAT congestion control seeks to:
1. utilize end-to-end available bandwidth, and maintain low queueing
delay when no other traffic is present,
2. add little to the queuing delay induced by concurrent TCP flows,
3. quickly yield to flows using standard TCP congestion control that
share the same bottleneck link,
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2.2. Applicability
LEDBAT is a "scavenger" congestion control mechanism that is
primarily motivated 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 seeks to operate in networks with FIFO queues and with tail-
drop queue management. Further study is required to understand the
implications of Active Queue Management (AQM) schemes on LEDBAT
mechanisms.
LEDBAT, as specified in this document, is a congestion control
mechanism that can be used as part of a transport protocol or as part
of an application. LEDBAT can be used where the data transmission
mechanisms are capable of carrying timestamps and acknowledging data
frequently. LEDBAT can be used, with appropriate extensions where
necessary, with TCP, SCTP, and DCCP, and with proprietary application
protocols such as those built atop UDP for P2P applications.
3. LEDBAT Congestion Control
3.1. Overview
A standard TCP sender increases its congestion window until a loss
occurs [RFC5681], which, in the absence of any Active Queue
Management (AQM) in the network, occurs only when the queue at the
bottleneck link on the end-to-end path overflows. Since packet loss
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 pre-determined
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 a
pre-determined target, LEDBAT decreases its sending rate quickly as a
response to potential congestion in the network.
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3.2. 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 roundtrip 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 3.5.)
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.
3.3. Receiver-Side Operation
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()
A receiver MAY send more than one delay sample in an acknowledgment.
For instance, a receiver that delays acknowledgments, i.e., sends an
acknowledgment less frequently than once per data packet, MAY send
all the one-way delay samples that it gathers in one acknowledgment.
3.4. Sender-Side Operation
3.4.1. An Overview
As a first approximation, a LEDAT sender operates as shown below; the
complete algorithm is specified later in Section 3.4.2. TARGET is
the maximum queueing delay that LEDBAT itself can introduce in the
network, and GAIN determines the rate at which the cwnd responds to
changes in queueing delay; both constants are specified later. Since
off_target can be positive or negative, the cwnd increases or
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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
acknowledgment, noise filtering, base delay expiration, and sender
idle times, which we now take into account in our complete sender
algorithm below.
3.4.2. The Complete Sender Algorithm
update_current_delay() maintains a list of one-way delay
measurements, of which the minimum 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.
This algorithm restricts cwnd growth after a period of inactivity,
where the cwnd is clamped down to a little more than flightsize using
max_allowed_cwnd. To be TCP-friendly on data loss, LEDBAT halves its
cwnd. The full sender-side algorithm is given below:
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on initialization:
create current_delays list with CURRENT_FILTER elements
create base_delays list with BASE_HISTORY number of elements
inialize elements in current_delays and base_delays to +INFINITY
last_rollover = -INFINITY # More than a minute in the past
cwnd = INIT_CWND * MSS
on acknowledgement:
# flightsize is the amount of data oustanding before this ack
# was received and is updated later by update_flightsize();
# bytes_newly_acked is the number of bytes that this ack
# newly acknowledges, and it MAY be set to MSS; and
# cwnd is in bytes.
for each delay sample in the acknowledgment:
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)
update_flightsize() #subtracts bytes_newly_acked from flightsize
on data loss:
# atmost once per RTT
cwnd = max(cwnd/2, MIN_CWND * MSS)
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.
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)
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The LEDBAT sender ensures that any outliers in the current_delay
samples are eliminated by implementing FILTER() to extract the actual
delay estimate from the current_delay samples. An example of such a
filter is the Exponentially-Weighted Moving Average (EWMA) function.
To implement an approximate minimum over the last N minutes, a LEDBAT
sender stores BASE_HISTORY+1 separate minima---one each for the last
BASE_HISTORY 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 is 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.
We note that LEDBAT assumes random fluctuations in inter-packet
transmission times; see section Section 5.3 for a discussion.
3.5. Parameter Values
TARGET MUST be 100 milliseconds or less, and this choice of value is
explained further in Section 4.3. Note that using the same TARGET
value across LEDBAT flows enables equitable sharing of the bottleneck
bandwidth---flows with a higher TARGET 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 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
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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. A
LEDBAT sender uses the current_delays list to maintain 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 depends on 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, we recommend that the sender SHOULD use at least
4 samples in each RTT. Thus, CURRENT_FILTER SHOULD be at least 4,
and limited such that no samples in list are older than an RTT in the
past.
MIN_CWND SHOULD be 2, and it MUST be at least 1. INIT_CWND SHOULD be
2, and it MUST be at least 1. The choice of MIN_CWND and INIT_CWND
are strongly connected to the framing protocol; a larger MIN_CWND
and/or INIT_CWND MAY be used if the framing protocol allows it. For
instance, TCP senders may use a larger INIT_CWND as specified in
[RFC3390].
4. Understanding LEDBAT Mechanisms
This section describes the delay estimation and window management
mechanisms used in LEDBAT.
4.1. Delay Estimation
LEDBAT estimates congestion in the direction of the data flow, and to
avoid measuring queue build-up on the reverse path (or ack path),
LEDBAT uses one-way delay estimates. LEDBAT assumes 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.
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4.1.1. 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. Using the minimum observed delay also allows LEDBAT to
eliminate noise in the delay estimation, such as due to spikes in
processing delay at a node on the 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
tradeoff 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.
4.1.2. Estimating Queueing Delay
Given that the base delay is constant, 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.
4.2. Managing the Congestion Window
4.2.1. Window Increase: Probing For More Bandwidth
A LEDBAT sender increases its congestion window if the queuing delay
is smaller than a target value, proportionally to the relative
difference between the current queueing delay and the delay target.
To be friendly to competing TCP flows, we set this highest rate of
window growth to be the same as TCP's. In other words, A LEDBAT flow
thus never ramps up faster than a competing TCP flow over the same
path.
4.2.2. Window Decrease: Responding To Congestion
When the sender's queueing delay estimate is higher than the target,
the LEDBAT flow's rate should be reduced. LEDBAT uses a simple
linear controller to detemine sending rate as a function of the delay
estimate, where the response is proportional to the difference
between the current queueing delay estimate and the target. In
limited experiments with Bittorrent nodes, this controller seems to
work well.
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Unlike TCP-like loss-based congestion control, LEDBAT does not induce
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.
4.3. Choosing The Queuing Delay Target
The queueing delay target is a tradeoff. A target that is too low
might result in under-utilization of the bottleneck link, especially
if the LEDBAT flow is the only flow on the link, and may also be more
sensitive to error in the measured delay. The International
Telecommunication Union's (ITU's) Recommendation G.114 defines a
delay of 150 ms to be acceptable for most user voice applications.
Thus the extra delay induced by LEDBAT must be below 150 ms to reduce
impact on delay-sentive applications.
Our recommendation of 100 ms or less as the target is based on these
considerations. Anecdotal evidence indicates that this value works
well: LEDBAT has been been implemented and successfully deployed with
a target value of 100 ms in two Bittorrent implementations---
BitTorrent DNA as the exclusive congestion control mechanism and in
uTorrent as an experimental mechanism.
5. Discussion
5.1. 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.
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5.2. Competing With TCP Flows
LEDBAT is designed to respond to congestion indications earlier than
loss-based TCP. A LEDBAT flow is more aggressive when the queueing
delay estimate is lower; since the queueing delay estimate is non-
negative, LEDBAT is most aggressive when its queuing delay estimate
is zero. In this case, LEDBAT ramps up its congestion window at the
same rate as TCP does. LEDBAT reduces its rate earlier than TCP
does, always halving the congestion window on loss. Thus, in the
worst case where the delay estimates are completely and consistently
off, a LEDBAT flow falls back to TCP mechanisms and is as aggressive
as a TCP flow.
5.3. Fairness Among LEDBAT Flows
The primary design goals of LEDBAT are focussed 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 some amount of
randomness in the inter-packet transmission times exist, as explained
further below.
Delay-based congestion control systems suffer from the possibility of
late-comers incorrectly measuring and using a higher base-delay than
an active flow that started earlier. Suppose a LEDBAT flow is the
only flow on the bottleneck, which the flow saturates, steadily
maintaining the queueing delay at a target delay. When a new LEDBAT
flow arrives, it might incorrectly measure the current end-to-end
delay, including the queueing delay being maintained by the first
LEDBAT flow, as its base delay, and the incoming flow might now
effectively seek to build on top of the existing, already maximal
queueing delay. As the second flow builds up, the first flow sees
the true queueing delay and backs off, while the late-comer keeps
building up, using up the entire link's capacity; this advantage is
called the "late-comer's advantage".
In the worse 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
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queueing delay to the network.
This advantage can be reduced if the the first flow yields quickly
enough to empty the bottleneck queue faster than the incoming flow
increases its occupancy in the queue; as a result, the late-comer
might measure a delay closer to the base delay. While such a
reduction might be achieved through a multiplicative decrease of the
congestion window, this might cause stronger fluctuations in flow
throughput during steady state.
In practice, however, this concern seems 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 OS scheduling at the sender, processing delay at
the sender or any network node, and link contention. When such a gap
occurs while the late-comer is starting, base delay is immediately
correctly measured. With a small number of LEDBAT flows, system
noise seems to sufficiently regulate the late-comer's advantage.
6. IANA Considerations
There are no IANA considerations for this document.
7. Security Considerations
A network on the path might choose to cause higher delay measurements
than the real queuing delay so that LEDBAT backs off even when
there's no congestion present. While shaping of traffic into an
artificially narrow bottleneck by increasing the queueing delay
cannot be trivially counteracted, a protocol using LEDBAT should seek
to minimize the risk of such an attack by authenticating the
timestamp and delay fields in the packets.
8. 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.
9. References
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9.1. Normative References
[RFC2119] Bradner, S., "Key words for use in RFCs to Indicate
Requirement Levels", BCP 14, RFC 2119, March 1997.
[RFC3390] Allman, M., Floyd, S., and C. Partridge, "Increasing TCP's
Initial Window", RFC 3390, October 2002.
[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.
9.2. 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.
Appendix A. Timestamp errors
One-way delay measurement needs to deal with timestamp errors. We'll
use the same locally linear clock model and the same terminology as
Network Time Protocol (NTP). This model is valid for any
differentiable clocks. NTP uses the term "offset" to refer to
difference from true time and "skew" to refer to difference of clock
rate from the true rate. The clock will thus have a fixed offset
from the true time and a skew. We'll consider what we need to do
about the offset and the skew separately.
A.1. Clock offset
First, consider the case of zero skew. The offset of each of the two
clocks shows up as a fixed error in one-way delay measurement. The
difference of the offsets is the absolute error of the one-way delay
estimate. We won't use this estimate directly, however. We'll use
the difference between that and a base delay. Because the error
(difference of clock offsets) is the same for the current and base
delay, it cancels from the queuing delay estimate, which is what
we'll use. Clock offset is thus irrelevant to the design.
A.2. Clock skew
The clock skew manifests in a linearly changing error in the time
estimate. For a given pair of clocks, the difference in skews is the
skew of the one-way delay estimate. Unlike the offset, this no
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longer cancels in the computation of the queuing delay estimate. On
the other hand, while the offset could be huge, with some clocks off
by minutes or even hours or more, the skew is typically small. For
example, NTP is designed to work with most clocks, yet it gives up
when the skew is more than 500 parts per million (PPM). Typical
skews of clocks that have never been trained seem to often be around
100-200 PPM. Previously trained clocks could have 10-20 PPM skew due
to temperature changes. A 100-PPM skew means accumulating 6
milliseconds of error per minute. The base delay updates mostly
takes care of clock skew unless the skew is unusually high or extreme
values have been chosen for TARGET and BASE_HISTORY so that the clock
skew in BASE_DELAY minutes is larger than the TARGET.
Clock skew can be in two directions: either the sender's clock is
faster than the receiver's, or vice versa.
If the senders's clock is faster the one-way delay measurement will
get more and more reduced by the clock drift over time. Whenever
there is no additional delay the base delay will be updated by a
smaller one-way delay value and the skew is compensated. This will
happen continuously as LEBDAT is design to keep the queue empty. If
a competing flow introduces additional queueing delay LEDBAT will
anyway get out of the way quickly and an overestimated one-way delay
will just speed-up the back-off.
When the receiver clock runs faster, the raw delay estimate will
drift up with time. This can suppress the throughput unnecessarily.
In this case a skew correction mechanim can be benefital. Further
condersiderations based on a deployed implementation and LEDBAT
specific preconditions are given in the next section.
A.3. Clock skew correction mechanism
The following paragraph describes the deployed clock skew correction
mechanism in the BitTorrent implementation for documentation purpose.
In the BitTorrent implemtation the receiver sends back the raw
(sending and receiving) timestamps. Based on this imfomation and the
system time at feedback receiption the sender can estimated the one-
way delay in both directions. Thus the sender can run the same base
delay calculation algorithm it runs for itself for the receiver as
well. If the sender can detect the receiver reducing its base delay,
it can infer that this is due to clock drift. The sender can be
compensated for by increasing the it's base delay by the same amount.
To apply this mechanism symmetrical framing is need (i.e., same
information about delays transmitted in both way).
The following considerations can be used for an alternative
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implementation as a reference:
o Skew correction with faster virtual clock:
Since having a faster clock on the sender will continuousely
update the base delay, a faster virtual clock for sender
timestamping can be applied. This virual clock can be computed
from the default machine clock through a linear transformation.
E.g. with a 500 PPM speed-up the sender's clock is very likely to
be faster than any receiver's clock and thus LEDBAT will benefit
from the implicit correction when updating the base delay.
o Skew correction with estimating drift:
With LEDBAT the history of base delay minima is already kept for
each minute. This 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,
calculate 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 acts the
fastest, since the state is preserved between connections.
Authors' Addresses
Stanislav Shalunov
BitTorrent Inc
612 Howard St, Suite 400
San Francisco, CA 94105
USA
Email: shalunov@bittorrent.com
URI: http://shlang.com
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Greg Hazel
BitTorrent Inc
612 Howard St, Suite 400
San Francisco, CA 94105
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
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