wdiff draft-dukkipati-tcpm-tcp-loss-probe-00.txt draft-dukkipati-tcpm-tcp-loss-probe-01.txt

TCP Maintenance Working Group N. Dukkipati
Internet-Draft N. Cardwell
Intended status: Experimental Y. Cheng
Expires: January 10, August 29, 2013 M. Mathis
Google, Inc
July 09, 2012

TCP
February 25, 2013

Tail Loss Probe (TLP): An Algorithm for Fast Recovery of Tail Losses
draft-dukkipati-tcpm-tcp-loss-probe-00.txt
draft-dukkipati-tcpm-tcp-loss-probe-01.txt

Abstract

Retransmission timeouts are detrimental to application latency,
especially for short transfers such as Web transactions where
timeouts can often take longer than all of the rest of a transaction.
The primary cause of retransmission timeouts are lost segments at the
tail of transactions. This document describes an experimental
algorithm for TCP to quickly recover lost segments at the end of
transactions or when an entire window of data or acknowledgments are
lost. TCP Tail Loss Probe (TLP) is a sender-only algorithm that allows
the transport to recover tail losses through fast recovery as opposed
to lengthy retransmission timeouts. If a connection is not receiving
any acknowledgments for a certain period of time, TLP transmits the
last unacknowledged segment (loss probe). In the event of a tail
loss in the original transmissions, the acknowledgment from the loss
probe triggers SACK/FACK based fast recovery. TLP effectively avoids
long timeouts and thereby improves TCP performance.

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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This Internet-Draft will expire on January 10, August 29, 2013.

Copyright Notice
Copyright (c) 2012 2013 IETF Trust and the persons identified as the
document authors. All rights reserved.

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Table of Contents

1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . 3
1.1. Terminology . . . . . . . . . . . . . . . . . . . . . . . 5
2. Loss probe algorithm . . . . . . . . . . . . . . . . . . . . . 5
2.1. Pseudocode . . . . . . . . . . . . . . . . . . . . . . . . 6
2.2. FACK threshold based recovery . . . . . . . . . . . . . . 8
3. Detecting recovered losses . . . . . . . . . . . . . . . . . . 7 9
3.1. TLP Loss Detection: The Basic Idea . . . . . . . . . . . . 8 9
3.2. TLP Loss Detection: Algorithm Details . . . . . . . . . . 8 9
4. Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . 10 11
4.1. Unifying loss recoveries . . . . . . . . . . . . . . . . . 10 12
4.2. Recovery of any N-degree tail loss . . . . . . . . . . . . 11 12
5. Experiments with TLP . . . . . . . . . . . . . . . . . . . . . 13 14
6. Related work . . . . . . . . . . . . . . . . . . . . . . . . . 15 16
7. Security Considerations . . . . . . . . . . . . . . . . . . . 15 17
8. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 15 17
9. References . . . . . . . . . . . . . . . . . . . . . . . . . . 16 18
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . . 17 19

1. Introduction

Retransmission timeouts are detrimental to application latency,
especially for short transfers such as Web transactions where
timeouts can often take longer than all of the rest of a transaction.
This document describes an experimental algorithm, TCP Tail Loss Probe
(TLP), to invoke fast recovery for losses that would otherwise be
only recoverable through timeouts.

The Transmission Control Protocol (TCP) has two methods for
recovering lost segments. First, the fast retransmit algorithm
relies on incoming duplicate acknowledgments (ACKs), which indicate
that the receiver is missing some data. After a required number of
duplicate ACKs have arrived at the sender, it retransmits the first
unacknowledged segment and continues with a loss recovery algorithm
such as the SACK-based loss recovery [RFC3517]. [RFC6675]. If the fast
retransmit algorithm fails for any reason, TCP uses a retransmission
timeout as the last resort mechanism to recover lost segments. If an
ACK for a given segment is not received in a certain amount of time
called retransmission timeout (RTO), the segment is resent [RFC6298].

Timeouts can occur in a number of situations, such as the following:

(1) Drop tail at the end of transactions. Example: consider a
transfer of five segments sent on a connection that has a congestion
window of ten. Any degree of loss in the tail, such as segments four
and five, will only be recovered via a timeout.

(2) Mid-transaction loss of an entire window of data or ACKs. Unlike
(1) there is more data waiting to be sent. Example: consider a
transfer of four segments to be sent on a connection that has a
congestion window of two. If the sender transmits two segments and
both are lost then the loss will only be recovered via a timeout.

(3) Insufficient number of duplicate ACKs to trigger fast recovery at
sender. The early retransmit mechanism [RFC5827] addresses this
problem in certain special circumstances, by reducing the number of
duplicate ACKs required to trigger a fast retransmission.

(4) An unexpectedly long round-trip time (RTT), such that the ACKs
arrive after the RTO timer expires. The F-RTO algorithm [RFC5682] is
designed to detect such spurious retransmission timeouts and at least
partially undo the consequences of such events.

Measurements on Google Web servers show that approximately 70% of
retransmissions for Web transfers are sent after the RTO timer
expires, while only 30% are handled by fast recovery. Even on
servers exclusively serving YouTube videos, RTO based retransmissions
account for about 46% of the retransmissions. If the losses are
detectable from the ACK stream (through duplicate ACKs or SACK
blocks) then early retransmit, fast recovery and proportional rate
reduction are effective in avoiding timeouts [IMC11PRR]. Timeout
retransmissions that occur in recovery and disorder state (a state
indicating that a connection has received some duplicate ACKs),
account for just 4% of the timeout episodes. On the other hand 96%
of the timeout episodes occur without any preceding duplicate ACKs or
other indication of losses at the sender [IMC11PRR]. Early
retransmit and fast recovery have no hope of repairing losses without
these indications. Efficiently addressing situations that would
cause timeouts without any prior indication of losses is a
significant opportunity for additional improvements to loss recovery.

To get a sense of just how long the RTOs are in relation to
connection RTTs, following is the distribution of RTO/RTT values on
Google Web servers. [percentile, RTO/RTT]: [50th percentile, 4.3];
[75th percentile, 11.3]; [90th percentile, 28.9]; [95th percentile,
53.9]; [99th percentile, 214]. Large RTOs, typically caused by
variance in measured RTTs, can be a result of intermediate queuing,
and service variability in mobile channels. Such large RTOs make a
huge contribution to the long tail on the latency statistics of short
flows. Note that simply reducing the length of RTO does not address
the latency problem for two reasons: first, it increases the chances
of spurious retransmissions. Second and more importantly, an RTO
reduces TCP's congestion window to one and forces a slow start.
Recovery of losses without relying primarily on the RTO mechanism is
beneficial for short TCP transfers.

The question we address in this document is: Can a TCP sender recover
tail losses of transactions through fast recovery and thereby avoid
lengthy retransmission timeouts? We specify an algorithm, TCP Tail Loss
Probe (TLP), which sends probe segments to trigger duplicate ACKs
with the intent of invoking fast recovery more quickly than an RTO at
the end of a transaction. TLP is applicable only for connections in
Open state, wherein a sender is receiving in-sequence ACKs and has
not detected any lost segments. TLP can be implemented by modifying
only the TCP sender, and does not require any TCP options or changes
to the receiver for its operation. For convenience, this document
mostly refers to TCP, but the algorithms and other discussion are
valid for Stream Control Transmission Protocol (SCTP) as well.

This document is organized as follows. Section 2 describes the basic
Loss Probe algorithm. Section 3 outlines an algorithm to detect the
cases when TLP plugs a hole in the sender. The algorithm makes the
sender aware that a loss had occurred so it performs the appropriate
congestion window reduction. Section 4 discusses the interaction of
TLP with early retransmit. retransmit in being able to recover any degree of tail
losses. Section 5 discusses the experimental results with TLP on
Google Web servers. Section 6 discusses related work, and Section 7
discusses the security considerations.

1.1. Terminology

The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT",
"SHOULD", "SHOULD NOT", "RECOMMENDED", "MAY", and "OPTIONAL" in this
document are to be interpreted as described in [RFC2119].

2. Loss probe algorithm

The Loss probe algorithm is designed for a sender to quickly detect
tail losses without waiting for an RTO. We will henceforth use tail
loss to generally refer to either drops at the tail end of
transactions or a loss of an entire window of data/ACKs. TLP works
for senders with SACK enabled and in Open state, i.e. the sender has
so far received in-sequence ACKs with no SACK blocks. The risk of a
sender incurring a timeout is high when the sender has not received
any ACKs for a certain portion of time but is unable to transmit any
further data either because it is application limited (out of new
data to send), receiver window (rwnd) limited, or congestion window
(cwnd) limited. For these circumstances, the basic idea of TLP is to
transmit probe segments for the specific purpose of eliciting
additional ACKs from the receiver. The initial idea was to send some
form of zero window probe (ZWP) with one byte of new or old data.
The ACK from the ZWP would provide an additional opportunity for a
SACK block to detect loss without an RTO. Additional losses can be
detected subsequently and repaired as SACK based fast recovery
proceeds. However, in practice sending a single byte of data turned
out to be problematic to implement and more fragile than necessary.
Instead we use a full segment to probe but have to add complexity to
compensate for the probe itself masking losses.

Define probe timeout (PTO) to be a timer event indicating that an ACK
is overdue on a connection. The PTO value is set to max(2 * SRTT,
10ms), where SRTT is the smoothed round-trip time [RFC6298], and is
adjusted to account for delayed ACK timer when there is only one
outstanding segment.

The basic version of the TLP algorithm transmits one probe segment
after a probe timeout if the connection has outstanding
unacknowledged data but is otherwise idle, i.e. not receiving any
ACKs or is cwnd/rwnd/application limited. The transmitted segment,
aka loss probe, can be either a new segment if available and the
receive window permits, or a retransmission of the most recently sent
segment, i.e., the segment with the highest sequence number. When
there is tail loss, the ACK from the probe triggers fast recovery.
In the absence of loss, there is no change in the congestion control
or loss recovery state of the connection, apart from any state
related to TLP itself.

TLP MUST NOT be used for non-SACK connections. SACK feedback allows
senders to use the algorithm described in section 3 to infer whether
any segments were lost.

2.1. Pseudocode

We define the terminology used in specifying the TLP algorithm:

FlightSize: amount of outstanding data in the network as defined in
[RFC5681].

RTO: The transport's retransmission timeout (RTO) is based on
measured round-trip times (RTT) between the sender and receiver, as
specified in [RFC6298] for TCP.

PTO: Probe timeout is a timer event indicating that an ACK is
overdue. Its value is constrained to be smaller than or equal to an
RTO.

SRTT: smoothed round-trip time computed like in [RFC6298].

Open state: the sender has so far received in-sequence ACKs with no
SACK blocks, and no other indications (such as retransmission
timeout) that a loss may have occurred.

Consecutive PTOs: back-to-back PTOs all scheduled for the same tail
packets in a flight. The (N+1)st PTO is scheduled after transmitting
the probe segment for Nth PTO.

The TLP algorithm works as follows:

(1) Schedule PTO after transmission of new data in Open state:

Check for conditions to schedule PTO outlined in step 2 below.
FlightSize > 1: schedule PTO in max(2*SRTT, 10ms).
FlightSize == 1: schedule PTO in max(2*SRTT, 1.5*SRTT+WCDelAckT).
If RTO is earlier, schedule PTO in its place: PTO = min(RTO, PTO).

WCDelAckT stands for worst case delayed ACK timer. When FlightSize
is 1, PTO is inflated additionally by WCDelAckT time to compensate
for a potential long delayed ACK timer at the receiver. The
RECOMMENDED value for WCDelAckT is 200ms.

A PTO value of 2*SRTT allows a sender to wait long enough to know
that an ACK is overdue. Under normal circumstances, i.e. no losses,
an ACK typically arrives in one RTT. But choosing PTO to be exactly
an RTT is likely to generate spurious probes given that even end-
system timings can easily push an ACK to be above an RTT. We chose
PTO to be the next integral value of RTT. If RTO is smaller than the
computed value for PTO, then a probe is scheduled to be sent at the
RTO time. The RTO timer is rearmed at the time of sending the probe,
as is shown in Step 3 below. This ensures that a PTO is always sent
prior to a connection experiencing an RTO.

(2) Conditions for scheduling PTO:

(a) Connection is in Open state.
(b) RTO is farther than PTO.
(c) Connection is either cwnd limited or application limited.
(d)
(c) Number of consecutive PTOs <= 2.
(e)
(d) Connection is SACK enabled.

Implementations MAY use one or two consecutive PTOs.

(3) When PTO fires:

(a) If a new previously unsent segment exists:
-> Transmit new segment.
-> FlightSize += SMSS. cwnd remains unchanged.
(b) If no new segment exists:
-> Retransmit the last segment.
(c) Reschedule next PTO if Increment statistics counter for loss probes.
(d) If conditions in (2) allow. are satisfied:
-> Reschedule next PTO.
Else:
-> Rearm RTO to fire at epoch 'now+RTO'.

The reason for retransmitting the last segment in Step (b) is so that
the ACK will carry SACK blocks and trigger either SACK-based loss
recovery [RFC3517] [RFC6675] or FACK-based FACK threshold based fast recovery [FACK]. On
transmission of a TLP, a MIB counter is incremented to keep track of
the total number of loss probes sent.

(4) During ACK processing:

Cancel any existing PTO.
If conditions in (2) allow:
-> Reschedule the PTO relative to the
time at which the ACK is received. receipt time.

Following is an example of TLP. All events listed are at a TCP
sender.

(1) Sender transmits segments 1-10: 1, 2, 3, ..., 8, 9, 10. There is
no more new data to transmit. A PTO is scheduled to fire in 2 RTTs,
after the transmission of the 10th segment.

(2) Receives acknowledgements (ACKs) for segments 1-5; segments 6-10
are lost and no ACKs are received. Note that the sender
(re)schedules its PTO timer relative to the last received ACK, which
is the ACK for segment 5 in this case. The sender sets the PTO
interval using the calculation described in step (1) of the
algorithm.

(3) When PTO fires, sender retransmits segment 10.

(4) After an RTT, SACK for packet 10 arrives. The ACK also carries
SACK holes for segments 6, 7, 8 and 9. This triggers FACK-based FACK threshold
based recovery.

(5) Connection enters fast recovery and retransmits remaining lost
segments.

2.2. FACK threshold based recovery

At the core of TLP is its reliance on FACK threshold based algorithm
to invoke Fast Recovery. In this section we specify this algorithm.

Section 3.1 of the Forward Acknowledgement (FACK) Paper [FACK]
describes an alternate algorithm for triggering fast retransmit,
based on the extent of the SACK scoreboard. Its goal is to trigger
fast retransmit as soon as the receiver's reassembly queue is larger
than the dupack threshold, as indicated by the difference between the
forward most SACK block edge and SND.UNA. This algorithm quickly and
reliably triggers fast retransmit in the presence of burst losses --
often on the first SACK following such a loss. Such a threshold
based algorithm also triggers fast retransmit immediately in the
presence of any reordering with extent greater than the dupack
threshold.

FACK threshold based recovery works by introducing a new TCP state
variable at the sender called SND.FACK. SND.FACK reflects the
forward-most data held by the receiver and is updated when a SACK
block is received acknowledging data with a higher sequence number
than the current value of SND.FACK. SND.FACK reflects the highest
sequence number known to have been received plus one. Note that in
non-recovery states, SND.FACK is the same as SND.UNA. The following
snippet is the pseudocode for FACK threshold based recovery.

If (SND.FACK - SND.UNA) > dupack threshold:
-> Invoke Fast Retransmit and Fast Recovery.

3. Detecting recovered losses

If the only loss was the last segment, there is the risk that the
loss probe itself might repair the loss, effectively masking it from
congestion control. To avoid interfering with mandatory congestion
control [RFC5681] it is imperative that TLP include a mechanism to
detect when the probe might have masked a loss and to properly reduce
the congestion window (cwnd). An algorithm to examine subsequent
ACKs to determine whether the original segment was lost is described
here.

Since it is observed that a significant fraction of the hosts that
support SACK do not support duplicate selective acknowledgments
(D-SACKs) [RFC2883] the TLP algorithm for detecting such lost
segments relies only on basic RFC 2018 SACK [RFC2018].

3.1. TLP Loss Detection: The Basic Idea

Consider a TLP retransmission "episode" where a sender retransmits N
consecutive TLP packets, all for the same tail packet in a flight.
Let us say that an episode ends when the sender receives an ACK above
the SND.NXT at the time of the episode. We want to make sure that
before the episode ends the sender receives N "TLP dupacks",
indicating that all N TLP probe segments were unnecessary, so there
was no loss/hole that needed plugging. If the sender gets less than
N "TLP dupacks" before the end of the episode, then probably the
first TLP packet to arrive at the receiver plugged a hole, and only
the remaining TLP packets that arrived at the receiver generated
dupacks.

Note that delayed ACKs complicate the picture, since a delayed ACK
will imply that the sender receives one fewer ACK than would normally
be expected. To mitigate this complication, before sending a TLP
loss probe retransmission, the sender should attempt to wait long
enough that the receiver has sent any delayed ACKs that it is
withholding. The sender algorithm, described in section 2.1 features
such a delay.

If there is ACK loss or a delayed ACK, then this algorithm is
conservative, because the sender will reduce cwnd when in fact there
was no packet loss. In practice this is acceptable, and potentially
even desirable: if there is reverse path congestion then reducing
cwnd is prudent.

3.2. TLP Loss Detection: Algorithm Details

(1) State
TLPRtxOut: the number of unacknowledged TLP retransmissions in
current TLP episode. The connection maintains this integer counter
that tracks the number of TLP retransmissions in the current episode
for which we have not yet received a "TLP dupack". The sender
initializes the TLPRtxOut field to 0.

TLPHighRxt: the value of SND.NXT at the time of TLP retransmission.
The TLP sender uses TLPHighRxt to record SND.NXT at the time it
starts doing TLP transmissions during a given TLP episode.

(2) Initialization

When a connection enters the ESTABLISHED state, or suffers a
retransmission timeout, or enters fast recovery, it executes the
following:

TLPRtxOut = 0;
TLPHighRxt = 0;

(3) Upon sending a TLP retransmission:

if (TLPRtxOut == 0)
TLPHighRxt = SND.NXT;
TLPRtxOut++;

(4) Upon receiving an ACK:

(a) Tracking ACKs

We define a "TLP dupack" as a dupack that has all the regular
properties of a dupack that can trigger fast retransmit, plus the ACK
acknowledges TLPHighRxt, and the ACK carries no new SACK information
(as noted earlier, TLP requires that the receiver supports SACK).
This is the kind of ACK we expect to see for a TLP transmission if
there were no losses. More precisely, the TLP sender considers a TLP
probe segment as acknowledged if all of the following conditions are
met:

(a) TLPRtxOut > 0
(b) SEG.ACK == TLPHighRxt
(c) the segment contains no SACK blocks for sequence ranges
above TLPHighRxt
(d) the ACK does not advance SND.UNA
(e) the segment contains no data
(f) the segment is not a window update

If all of those conditions are met, then the sender executes the
following:

TLPRtxOut--;

(b) Marking the end of a TLP episode and detecting losses

If an incoming ACK is after TLPHighRxt, then the sender deems the TLP
episode over. At that time, the TLP sender executes the following:

isLoss = (TLPRtxOut > 0); 0) &&
(segment does not carry a DSACK for TLP retransmission);
TLPRtxOut = 0
if (isLoss)
EnterRecovery();

In other words, if the sender detects an ACK for data beyond the TLP
loss probe retransmission then (in the absence of reordering on the
return path of ACKs) it should have received any ACKs that will
indicate whether the original or any loss probe retransmissions were
lost. An exception is the case when the segment carries a Duplicate
SACK (DSACK) for the TLP retransmission. If the TLPRtxOut count is
still non-zero and thus indicates that some TLP probe segments remain
unacknowledged, then the sender should presume that at least one
segment was lost, so it should enter fast recovery using the
proportional rate reduction algorithm [IMC11PRR].

(5) Senders must only send a TLP loss probe retransmission if all the
conditions from section 2.1 are met and the following condition also
holds:

(TLPRtxOut == 0) || (SND.NXT == TLPHighRxt)

This ensures that there is at most one sequence range with
outstanding TLP retransmissions. The sender maintains this invariant
so that there is at most one TLP retransmission "episode" happening
at a time, so that the sender can use the algorithm described above
in this section to determine when the episode is over, and thus when
it can infer whether any data segments were lost.

Note that this condition only limits the number of outstanding TLP
loss probes that are retransmissions. There may be an arbitrary
number of outstanding unacknowledged TLP loss probes that consist of
new, previously-unsent data, since the standard retransmission
timeout and fast recovery algorithms are sufficient to detect losses
of such probe segments.

4. Discussion

In this section we discuss two properties related to TLP.

4.1. Unifying loss recoveries

The existing loss recovery algorithms in TCP have a discontinuity: A
single segment loss in the middle of a packet train can be recovered
via fast recovery while a loss at the end of the train causes an RTO.
Example: consider a train of segments 1-10, loss of segment five can
be recovered quickly through fast recovery, while loss of segment ten
can only be recovered through a timeout. In practice, the difference
between losses that trigger RTO versus those invoking fast recovery
has more to do with the position of the losses as opposed to the
intensity or magnitude of congestion at the link.

TLP unifies the loss recovery mechanisms regardless of the position
of a loss, so now with TLP a segment loss in the middle of a train as
well as at the tail end can now trigger the same fast recovery
mechanisms.

4.2. Recovery of any N-degree tail loss

The TLP algorithm, when combined with a variant of the early
retransmit mechanism described below, is capable of recovering any
tail loss for any sized flow using fast recovery.

We propose the following enhancement to the early retransmit
algorithm described in [RFC5827]: in addition to allowing an early
retransmit in the scenarios described in [RFC5827], we propose to
allow a delayed early retransmit [IMC11PRR] in the case where there
are three outstanding segments that have not been cumulatively
acknowledged and one segment that has been fully SACKed.

Consider the following scenario, which illustrates an example of how
this enhancement allows quick loss recovery in a new scenario:

(1) scoreboard reads: A _ _ _
(2) TLP retransmission probe of the last (fourth) segment
(3) the arrival of a SACK for the last segment changes
scoreboard to: A _ _ S
(4) early retransmit and fast recovery of the second and
third segments

With this enhancement to the early retransmit mechanism, then for any
degree of N-segment tail loss we get a quick recovery mechanism
instead of an RTO.

Consider the following taxonomy of tail loss scenarios, and the
ultimate outcome in each case:

number of scoreboard after
losses TLP retrans ACKed mechanism final outcome
-------- ----------------- ----------------- -------------
(1) AAAL AAAA TLP loss detection all repaired
(2) AALL AALS early retransmit all repaired
(3) ALLL ALLS early retransmit all repaired
(4) LLLL LLLS FACK fast recovery all repaired
(5) >=5 L ..LS FACK fast recovery all repaired

key:
A = ACKed segment
L = lost segment
S = SACKed segment

Let us consider each tail loss scenario in more detail:

(1) With one segment lost, the TLP loss probe itself will repair the
loss. In this case, the sender's TLP loss detection algorithm will
notice that a segment was lost and repaired, and reduce its
congestion window in response to the loss.

(2) With two segments lost, the TLP loss probe itself is not enough
to repair the loss. However, when the SACK for the loss probe
arrives at the sender, then the early retransmit mechanism described
in [RFC5827] will note that with two segments outstanding and the
second one SACKed, the sender should retransmit the first segment.
This retransmit will repair the single remaining lost segment.

(3) With three segments lost, the TLP loss probe itself is not enough
to repair the loss. However, when the SACK for the loss probe
arrives at the sender, then the enhanced early retransmit mechanism
described in this section will note that with three segments
outstanding and the third one SACKed, the sender should retransmit
the first segment and enter fast recovery. The early retransmit and
fast recovery phase will, together, repair the the remaining two lost
segments.

(4) With four segments lost, the TLP loss probe itself is not enough
to repair the loss. However, when the SACK for the loss probe
arrives at the sender, then the FACK fast retransmit mechanism [FACK]
will note that with four segments outstanding and the fourth one
SACKed, the sender should retransmit the first segment and enter fast
recovery. The fast retransmit and fast recovery phase will,
together, repair the the remaining two lost segments.

(5) With five or more segments lost, events precede much as in case
(4). The TLP loss probe itself is not enough to repair the loss.

However, when the SACK for the loss probe arrives at the sender, then
the FACK fast retransmit mechanism [FACK] will note that with five or
more segments outstanding and the segment highest in sequence space
SACKed, the sender should retransmit the first segment and enter fast
recovery. The fast retransmit and fast recovery phase will,
together, repair the remaining lost segments.

In summary, the TLP mechanism, in conjunction with the proposed
enhancement to the early retransmit mechanism, is able to recover
from a tail loss of any number of segments without resort to a costly
RTO.

5. Experiments with TLP

In this section we describe experiments and measurements with TLP
performed on Google Web servers using Linux 2.6. The experiments
were performed over several weeks and measurements were taken across
a wide range of Google applications. The main goal of the
experiments is to instrument and measure TLP's performance relative
to the baseline. The experiment and baseline were using the same
kernels with an on/off switch to enable TLP.

All

Our experiments were conducted with include both the basic version of the TLP
described algorithm of Section 2 and
its loss detection component in Section 2. 3. All other algorithms such
as early retransmit and FACK threshold based recovery are present in
the both the experiment and baseline. We have also experimented with a few
variations of TLP such as the consecutive probe segments to transmit
and the value that a PTO should be delayed by to take into account
delayed ACK timer when FlightSize equals one. The numbers reported
below are with experiments where we did not restrict the number of
consecutive probe segments to two. There are three primary
metrics we are interested in: impact on TCP latency (average and tail
or 99th percentile latency), retransmission statistics, and the percentage
overhead of probe segments relative to the total number of
transmitted segments. TCP latency is the time elapsed between the
server transmitting the first byte of the response to it receiving an
ACK for the last byte.

The probe segments are not accounted in retransmission statistics but
instead tracked separately in table below shows the Linux MIB.

Over percentiles and average latency improvement
of key Web applications, including even those responses without
losses, measured over a period of a week long experiment, TLP reduced one week. The key takeaway is: the
average TCP
latency of Google Web search response time improved up to 7% and Instant search by [average:3%, 99th
percentile:5%], Google Maps by [average:5%, the 99th percentile:10%], and
Google Images percentile
improved by [average:7%, 99th percentile:10%]. The varying
percentage of improvements is because 10%. Nearly all of the differences improvement for TLP is in the
response size distribution amongst
tail latency (post-90th percentile). The varied improvements across
services are due to different response-size distributions and traffic
patterns. For example, TLP helps the most for Images, as these services, e.g. Google
Images has are
served by multiple concurrently active TCP connections which increase
the smallest response sizes and hence is more prone to chances of tail segment losses.

Application Average 99%

Google Web Search -3% -5%

Google Maps -5% -10%

Google Images -7% -10%

TLP also improved performance in mobile
networks, e.g. networks -- by 7.2% for Web
search and Instant and 7.6% for Images transferred over Verizon
network. To see why and where the latency improvements are coming
from, we measured the retransmission statistics. We broke down the
retransmission stats based on nature of retransmission - -- timeout
retransmission or fast recovery. TLP reduced the number of timeout retransmissions timeouts
by 10% 15% compared to the baseline, i.e. (timeout_retrans_tlp (timeouts_tlp - timeout_retrans_baseline)
timeouts_baseline) /
timeout_retrans_baseline timeouts_baseline = 10%. This includes 15%. Instead, these losses
were either recovered via fast recovery or by the retransmissions
that occur loss probe
retransmission itself. The largest reduction in timeouts is when the slow start phase of the timeout. There
sender is a
corresponding increase in the number of fast retransmits Open state in which it receives only insequence ACKs
and no duplicate ACKs, likely because of tail losses.
Correspondingly, the retransmissions occurring in fast
recovery. the slow start
phase after RTO reduced by 46% relative to baseline. Note that it is
not always possible for TLP to convert 100% of the timeouts into fast
recovery episodes for two reasons:
either a PTO was not scheduled because an RTO was closer, or a probe
segment was sent but an RTO occurred anyway.

The overhead of probe segments as itself may be lost. Also notable
in our experiments is a percentage significant decrease in the number of
spurious timeouts -- the experiment had 61% fewer congestion window
undo events. The Linux TCP sender uses either DSACK or timestamps to
determine if retransmissions are spurious and employs techniques for
undoing congestion window reductions. We also note that the total
number of retransmissions decreased 7% with TLP because of the
decrease in spurious retransmissions, and because the TLP probe
itself plugs a hole.

We also quantified the overhead of probe packets. The probes
accounted for 0.48% of all outgoing segments is 0.6%, segments, i.e. (number of probe
segments / number of outgoing segments)*100 = 0.6%. When FlightSize equals 1 it 0.48%. This is
important to account for a
reasonable overhead when contrasted with the delayed ACK timer in overall retransmission
rate of 3.2%. 10% of the PTO value, in
order to bring down probes sent are new segments and the number of unnecessary probe segments. (the
WCDelAckT term, aka Worst Case delayed ACK time was set rest
are retransmissions, which is unsurprising given that short Web
responses often don't have new data to 200ms).
With delays send. We also found that in
about 33% of 0ms the cases, the probes themselves plugged the only hole
at receiver and 50ms, the percentage probe segments are 3.1% loss detection algorithm reduced the congestion
window. 37% of the probes were not necessary and 2.2% respectively. resulted in a
duplicate acknowledgment.

Besides the macro level latency and retransmission statistics, we
also measured
report some measurements from TCP's internal state variables at the
point when PTO
timer fires and a probe segment is transmitted. We report a few of
these statistics here. We measured the number of probe segments sent
consecutively within a single timeout period. About 80% of the
segments were probes sent the first time within the timeout period
while the remaining were consecutive probes. 10% of the probe
segments are new previously untransmitted data while the remainder
are a retransmission of the last sent segment.

The distribution below shows the time period, normalized by the
connection RTT, between the PTO timer firing and the epoch when the
next RTO is scheduled. Note that the slack time period between a PTO
and RTO can be several tens of RTTs, possibly because of large RTOs
caused by variance in round-trip times.

percentile 25% 50% 75% 90% 99%

[normalized interval] 1.4 3.3 10.5 21 95 The following
distribution shows the FlightSize and congestion window values when a
PTO is scheduled. We note that cwnd is not the limiting factor and
that nearly all of the probe segments are sent within the congestion
window.

percentile 10% 25% 50% 75% 90% 99%

FlightSize 1 1 2 3 10 20
cwnd 5 10 10 10 17 44

We have also experimented with a few variations of TLP: multiple
probe segments versus single probe for the same tail loss episode,
and several values for WCDelAckT. Our experiments show that sending
just one probe suffices to get most (~90%) of latency benefits. The
experiment results reported in this section and our current
implementation limits number of probes to one, although the draft
itself allows up to two consecutive probes. We chose the worst case
delayed ack timer to be 200ms. When FlightSize equals 1 it is
important to account for the delayed ACK timer in the PTO value, in
order to bring down the number of unnecessary probe segments. With
delays of 0ms and 50ms, the probe overhead jumped from 0.48% to 3.1%
and 2.2% respectively. We have also experimented with transmitting
1-byte probe retransmissions as opposed to an entire MSS
retransmission probe. While this scheme has the advantage of not
requiring the loss detection algorithm outlined in Section 3, it
turned out to be problematic to implement correctly in certain TCP
stacks. Additionally, retransmitting 1-byte probe costs one more RTT
to recover single packet tail losses, which is detrimental for short
transfer latency.

6. Related work

TCP's long and conservative RTO recovery has long been identified as
the major performance bottleneck for latency-demanding applications.
A well-studied example is online gaming that requires reliability and
low latency but small bandwidth. [GRIWODZ06] shows that repeated
long RTO is the dominating performance bottleneck for game
responsiveness. The authors in [PETLUND08] propose to use linear RTO
to improve the performance, which has been incorporated in the Linux
kernel as a non-default socket option for such thin streams.
[MONDAL08] further argues exponential RTO backoff should be removed
because it is not necessary for the stability of Internet. In
contrast, TLP does not change the RTO timer calculation or the
exponential back off. TLP's approach is to keep the behavior after
RTO conservative for stability but allows a few timely probes before
concluding the network is badly congested and cwnd should fall to 1.

As noted earlier in the Introduction the F-RTO [RFC5682] algorithm
reduces the number of spurious timeout retransmissions and the Early
Retransmit [RFC5827] mechanism reduces timeouts when a connection has
received a certain number of duplicate ACKs. Both are complementary
to TLP and can work alongside.

TCP Rescue retransmission introduced in
[RFC6675] deals with loss events such as AL*SL* (using the same
notation as section 4). TLP covers wider range of events such as
AL*. We experimented with rescue retransmission on Google Web
servers, but did not observe much performance improvement. When the
last segment is lost, it is more likely that a number of contiguous
segments preceding the segment are also lost, i.e. AL* is common.
Timeouts that occur in the fast recovery are rare.

[HURTIG13] proposes to offset the elapsed time of the pending packet
when re-arming the RTO timer. It is possible to apply the same idea
for the TLP timer as well. We have not yet tested such a change to
TLP.

Tail Loss Probe is one of several algorithms designed to maximize the
robustness of TCPs self clock in the presence of losses. It follows
the same principles as Proportional Rate Reduction [IMC11PRR] and TCP
Laminar [Laminar].

On a final note we note that Tail loss probe does not eliminate 100%
of all RTOs. RTOs still remain the dominant mode of loss recovery
for short transfers. More work in future should be done along the
following lines: transmitting multiple loss probes prior to finally
resorting to RTOs, maintaining ACK clocking for short transfers in
the absence of new data by clocking out old data in response to
incoming ACKs, taking cues from applications to indicate end of
transactions and use it for smarter tail loss recovery.

7. Security Considerations

The security considerations outlined in [RFC5681] apply to this
document. At this time we did not find any additional security
problems with TCP Tail loss probe.

8. IANA Considerations

This document makes no request of IANA.

Note to RFC Editor: this section may be removed on publication as an
RFC.

9. References

[RFC3517]

[RFC6675] Blanton, E., Allman, M., Fall, K., and L. Wang, L., Jarvinen, I., Kojo, M.,
and Y. Nishida, "A Conservative Selective Acknowledgment (SACK)-based Loss Recovery Algorithm
Based on Selective Acknowledgment (SACK) for TCP",
RFC 3517, April 2003. 6675, August 2012.

[RFC6298] Paxson, V., Allman, M., Chu, J., and M. Sargent,
"Computing TCP's Retransmission Timer", RFC 6298,
June 2011.

[RFC5827] Allman, M., Ayesta, U., Wang, L., Blanton, J., and P.
Hurtig, "Early Retransmit for TCP and Stream Control
Transmission Protocol (SCTP)", RFC 5827, April 2010.

[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,
September 2009.

[IMC11PRR]
Mathis, M., Dukkipati, N., Cheng, Y., and M. Ghobadi,
"Proportional Rate Reduction for TCP", Proceedings of the
2011 ACM SIGCOMM conference on Internet measurement
conference , 2011.

[RFC2119] Bradner, S., "Key words for use in RFCs to Indicate
Requirement Levels", RFC 2119, March 1997.

[RFC5681] Allman, M., Paxson, V., and E. Blanton, "TCP Congestion
Control", RFC 5681, September 2009.

[FACK] Mathis, M. and M. Jamshid, "Forward acknowledgement:
refining TCP congestion control", ACM SIGCOMM Computer
Communication Review, Volume 26, Issue 4, Oct. 1996. ,
1996.

[RFC2883] Floyd, S., Mahdavi, J., Mathis, M., and M. Podolsky, "An
Extension to the Selective Acknowledgement (SACK) Option
for TCP", RFC 2883, July 2000.

[RFC2018] Mathis, M. and J. Mahdavi, "TCP Selective Acknowledgment
Options", RFC 2018, October 1996.

[GRIWODZ06]
Griwodz, C. and P. Halvorsen, "The fun of using TCP for an
MMORPG", NOSSDAV , 2006.

[PETLUND08]
Petlund, A., Evensen, K., Griwodz, C., and P. Halvorsen,
"TCP enhancements for interactive thin-stream
applications", NOSSDAV , 2008.

[MONDAL08]
Mondal, A. and A. Kuzmanovic, "Removing Exponential
Backoff from TCP", ACM SIGCOMM Computer Communication
Review , 2008.

[Laminar] Mathis, M., "Laminar TCP and the case for refactoring TCP
congestion control", draft-mathis-tcpm-tcp-laminar-00 July 2012.

[HURTIG13]
Hurtig, P., Brunstrom, A., Petlund, A., and M. Welzl, "TCP
and SCTP RTO Restart", draft-ietf-tcpm-rtorestart-00 (work
in progress), February 2012. 2013.

Authors' Addresses

Nandita Dukkipati
Google, Inc
1600 Amphitheater Parkway
Mountain View, California 93117
USA

Email: nanditad@google.com

Neal Cardwell
Google, Inc
76 Ninth Avenue
New York, NY 10011
USA

Email: ncardwell@google.com

Yuchung Cheng
Google, Inc
1600 Amphitheater Parkway
Mountain View, California 93117
USA

Email: ycheng@google.com
Matt Mathis
Google, Inc
1600 Amphitheater Parkway
Mountain View, California 93117
USA

Email: mattmathis@google.com