INTERNET-DRAFT Expires June 1999 INTERNET-DRAFT
Network Working Group Matt Mathis
INTERNET-DRAFT Pittsburgh Supercomputing Center
Expiration Date: June 1999 Mark Allman
NASA Lewis
Empirical Bulk Transfer Capacity
< draft-ietf-ippm-btc-framework-00.txt >
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This memo provides information for the Internet community. This memo
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Abstract:
Bulk Transport Capacity (BTC) is a measure of a network's ability
to transfer significant quantities of data with a single
congestion-aware transport connection (e.g., TCP). The intuitive
definition of BTC is the expected long term average data rate
(bits per second) of a single ideal TCP implementation over the
path in question. However, there are many congestion control
algorithms (and hence transport implementations) permitted by
IETF standards. This diversity in transport algorithms creates a
difficulty for standardizing BTC metrics because the allowed
diversity is sufficient to lead to situations where different
implementations will yield non-comparable measures -- and
potentially fail the formal tests for being a metric.
This document defines a framework for standardizing multiple BTC
metrics that parallel the permitted transport diversity. Two
approaches are used. First, each BTC metric must be much more
tightly specified than the typical IETF protocol. Pseudo-code or
reference implementations are expected to be the norm. Second,
each BTC methodology is expected to collect some ancillary metrics
which are potentially useful to support analytical models of BTC.
1. Introduction
Bulk Transport Capacity (BTC) is a measure of a network's ability
to transfer significant quantities of data with a single
congestion-aware transport connection (e.g., TCP). For many
applications the BTC of the underlying network dominates the
overall elapsed time for the application and thus dominates the
performance as perceived by a user. Examples of such
applications include FTP, and the world wide web when delivering
large images or documents.
The intuitive definition of BTC is the expected long term average
data rate (bits per second) of a single ideal TCP implementation
over the path in question.
Central to the notion of bulk transport capacity is the idea that
all transport protocols should have similar responses to
congestion in the Internet. Indeed the only form of equity
significantly deployed in the Internet today is that the vast
majority of all traffic is carried by TCP implementations sharing
common congestion control algorithms largely due to a shared
developmental heritage.
[RFC2001.bis] specifies the standard congestion control algorithms
used by these TCP implementations. Even though this document is a
(proposed) standard, it permits considerable latitude in
implementation. This latitude is by design, to encourage ongoing
evolution in congestion control algorithms.
This legal diversity in transport algorithms creates a
difficulty for standardizing BTC metrics because the allowed
diversity is sufficient to lead to situations where different
implementations will yield non-comparable measures -- and
potentially fail the formal tests for being a metric.
@@@ A more serious problem is that most of the existing CC algorithms
@ do not assure that improving the properties of a path improves the
@ measure of that path. That is existing TCP implementations do not
@ always have performance that monotonically increase with true path
@ capacity.
#
# OK. I'll leave that to you... I think it needs said and supported
# with some explanation. --allman
@ Next pass --MM--
Furthermore congestion control and related areas, including
Integrated services[@@], differentiated services[@@] and Internet
traffic analysis[@@] are all currently receiving a lot of
attention from the research community. It is very likely that we
will see new experimental congestion control algorithms in the near
future. In addition, explicit congestion notification (ECN)
[RFC98] is being tested for Internet deployment. We do not yet
know how any of these developments might affect BTC metrics.
This document defines a framework for standardizing multiple BTC
metrics that parallel the permitted transport diversity. Two
approaches are used. First, each BTC metric must be much more
tightly specified than the typical IETF protocol. Pseudo-code or
reference implementations are expected to be the norm. Second,
each BTC methodology is expected to collect some ancillary metrics
which are potentially useful to support analytical models of BTC.
For example, the models in [PFTK98, MSMO97, OKM96a, Lak94] all
predict bulk performance based on path properties such as loss
rate, round trip time, etc. A BTC methodology which also provides
ancillary measures of these properties is stronger because
agreement with the analytical models can be used to corroborate
the direct BTC measurement results.
More importantly these ancillary metrics are expected to be useful
for resolving disparity between different BTC metrics. For
example, a path that predominantly experiences clustered packet
losses is likely to exhibit vastly different measures from BTC
metrics that mimic Tahoe, Reno, NewReno, and SACK TCP
algorithms [FF96]. The differences in the BTC metrics over
such a path might be diagnosed by an ancillary measure of loss
clustering.
Furthermore there are some path properties which are best measured
as ancillary metrics to a transport protocol. Examples of such
properties include bottleneck queue limits or the tendency to
reorder packets. These are difficult or impossible to measure at
low rates and unsafe to measure at rates higher than the bulk
transport capacity of the path.
It is expected that at some point in the future there will exist
an A-frame [RFC2330] which will unify all simple path metrics
(e.g., segment loss rates, round trip time) and BTC ancillary
metrics (e.g. queue size and packet reordering) with different
versions of BTC metrics (e.g., that parallel Reno or SACK TCP).
2. Congestion Control Algorithms
Nearly all TCP implementations in use today are based on
congestion control algorithms published in [Jac88] and further
refined in [RFC2001,RFC2001.bis]. In addition to the basic notion
of using an ACK clock, TCP (and therefore BTC) implements five
standard congestion control algorithms: Congestion Avoidance,
Retransmission timeouts, Slow-start, Fast Retransmit and Fast
Recovery. All BTC implementations must use these algorithms as
they are defined in [RFC2001.bis]. However, in all cases a BTC
metric must more tightly specify these algorithms, as discussed
below.
2.1 Congestion Avoidance
The Congestion Avoidance algorithm drives the steady-state bulk
transfer behavior of TCP. It calls for opening the congestion
window (cwnd) by a constant additive amount during each round trip
time (RTT), and closing it by a constant multiplicative fraction
on congestion, as indicated by lost segments. The window closing
is specified to be half the number of outstanding data segments in
flight when loss is detected. A BTC metric must specify the
following Congestion Avoidance details:
The exact algorithm for incrementing cwnd is left to the
implementer. Several candidate algorithms are outlined in
[RFC2001.bis]. In addition, some of these algorithms include some
rounding. For these reasons, the exact algorithm for increasing
cwnd during congestion avoidance must be fully specified for
each BTC metric defined.
[RFC2001.bis] permits an extra plus one segment window
adjustment following the multiplicative closing of cwnd. This
is because [RFC2001.bis] allows a single invocation of the Slow-Start
algorithm when when cwnd equals ssthresh at the end of
recovery.
2.2 Retransmission Timeouts
In order to provide reliable data delivery, TCP resends a segment if
the ACK for the given segment does not arrive before the
retransmission timer (RTO) fires. A BTC metric must implement an
RTO timer to trigger retransmissions not handled by the fast
retransmit algorithm. Such retransmissions can have a large impact
on the measured capacity. Calculating the RTO is subject to a
number of details that are not standardized. When implementing a
BTC metric the details of the RTO calculation, how and when the
clock is set, as well as the clock granularity must be fully
documented.
2.3 Slow Start
Slow start is part of TCP's transient behavior. It is used to
quickly bring new or recently restarted connections up to an
appropriate congestion window. In addition, slow start is used to
restart the ACK clock after a retransmission timeout. A BTC
implementation must use the slow start algorithm, as specified by
[RFC2001.bis]. The slow start algorithm is used while the congestion
window (cwnd) is less than the slow start threshold (ssthresh).
However, whether to use slow start or congestion avoidance when cwnd
equals ssthresh is left to the implementer by [RFC2001.bis]. This
detail must be specified in every specific BTC metric definition.
2.4 Fast Retransmit/Fast Recovery
The Fast Retransmit/Fast Recovery algorithms are used to infer
segment loss before the RTO expires. A BTC implementation must
implement the algorithms as defined in [RFC2001.bis].
In Reno TCP, Fast Retransmit and Fast Recovery are used to support
the Congestion Avoidance algorithm during recovery from lost
segments. During Fast Recovery, the data receiver sends duplicated
acknowledgments. The data sender uses these duplicate ACKs to
detect loss, to estimate the quantity of data in the network still
pending delivery and to clock out new data in an effort to keep the
ACK clock running.
2.5 Advanced Recovery Algorithms
It has been observed that under some conditions the Fast
Retransmit and Fast Recovery algorithms do not reliably preserve
TCP's Self-Clock, causing unpredictable or unstable TCP
performance [Lak94@@@check, Flo95]. Simulations of reference TCP
implementations have uncovered situations where incidental changes
in other parts of the network have a large effect on performance
[MM96a]. Other simulations have shown that under some
conditions, slightly better networks (higher bandwidth, lower
delay or less load from other connections) yield lower throughput.
@@@ This is pretty easy to construct, but has it been published?
# Not that I can think of off the top of my head... Maybe a concrete
# example to back up the claim? --allman
[RFC2001.bis] allows a TCP implementation to use more robust loss
recovery algorithms, such as NewReno type algorithms
[FH98,FF96,Hoe96] and SACK-based algorithms [FF96,MM96a,MM96b].
While allowing these algorithms, [RFC2001.bis] does not define any
such algorithm and therefore, a BTC metric that implements
advanced recovery algorithms must fully specify the details.
Note that since TCP based on standard Fast Retransmit and Fast
Recovery sometimes exhibits erratic performance [MM96a], these
algorithms may prove to be unsuitable for use in a metric.
# Ouch... I know what you're saying, but... If the goal is to see what
# congestion-aware transport connection yields, I think the above is a
# little harsh given the current standardized CC algorithms.
2.6 Segment Size
The actual segment size, or method of choosing a segment size
(e.g., path MTU discovery [RFC1191]) and the number of header
bytes assumed to be prepended to each segment must be specified.
In addition if the segment size is artificially limited to less
than the path MTU this must be indicated.
3 Ancillary Metrics
The following ancillary metrics should be implemented in every BTC
that can exhibit the relevant behaviors. Alternatively, the BTC
implementation should provide enough information that the following
information can be gathered in post-processing (e.g., by providing a
segment trace of the connection).
3.1 Congestion Avoidance Capacity
Define a pure "Congestion Avoidance Capacity" (CAC) metric to be
the data rate (bits per second) of a fully specified
implementation of the Congestion Avoidance algorithm, subject to
the restriction that the Retransmission Timeout and Slow-Start
algorithms are not invoked. The CAC metric is defined to have no
meaning across Retransmission Timeouts or Slow-Start (except the
single segment Slow-Start that is permitted to follow recovery).
In principle a CAC metric would be an ideal BTC metric. But there
is a rather substantial difficulty with using it as such. The
Self-Clocking of the Congestion Avoidance algorithm can be very
fragile, depending on the specific details of the Fast Retransmit,
Fast Recovery or advanced recovery algorithms above.
When TCP looses Self-Clock it is reestablished through a
retransmission timeout and Slow-Start. These algorithms nearly
always take more time than Congestion Avoidance would have taken.
It is easily observed that unless the network loses an entire
window of data (which would clearly require a retransmit timeout)
TCP missed some opportunity to send data. That is, if TCP
experiences a timeout after losing any partial window of data, it
must have received at least one ACK that was generated after some
of the partial data was delivered, but did not trigger
transmitting any new data. Much recent research in congestion
control (e.g., FACK[MM96a], NewReno[FH98], [LowWindow]) can be
characterized as making TCP's Self-Clock more tenacious, while
preserving fairness under adverse conditions. This work is often
motivated by how poorly current TCP implementations perform under
some conditions, often due to repeated clock loss. Since this is
an active research area, different TCP implementations have rather
considerable differences in their ability to preserve Self-Clock.
3.2 Ancillary metrics relating to the preservation of Self-Clock
Since loosing the clock can have a large effect on the overall BTC,
and the clock is itself fragile in ways that are very dependent on
the recovery algorithm, it is important that the transitions between
timer driven and Self-Clocked operation be instrumented.
3.2.1 Lost transmission opportunities
If the last event before a timeout was the receipt of an ACK that
did not trigger a retransmission, the possibility exists that
some other congestion control algorithm would have successfully
preserved the Self-Clock. In this event, instrumenting key parts
of the BTC state (e.g., cwnd) may lead to further improvements in
congestion control algorithms.
Note that in the absence of knowledge about the future, it is not
possible to design an algorithm that never misses transmission
opportunities. However, there are ever more subtle ways to gauge
network state, and to estimate if a given ACK is likely to be the
last.
3.2.2 Loosing an entire window
If an entire window of data (or ACKs) is lost, there will be no
returning ACKs to clock out additional data. This condition can
be detected if the last event before a timeout was a data
transmission triggered by an ACK. The loss of an entire window
of data/ACKs forces recovery to be via a Retransmission Timeout and
Slow-Start.
Losing an entire window of data implies an outage with a duration
at least as long as a round trip time. Such an outage can not be
diagnosed with low rate metrics and is unsafe to diagnose at
higher rates than the BTC. Therefore all BTC metrics at should
instrument and report losses of an entire window of data.
There are some conditions, such as at very small window, in which
there is a significant probability that an entire window can be
legitimately lost through individual random losses.
3.2.3 Heroic clock preservation
All algorithms that permit a given BTC to sustain Self-Clock when
other algorithms might not, should be instrumented. Furthermore,
the details of the algorithms used must be fully documented.
BTC metrics that can sustain Self-Clock in the presence of
multiple losses within one round trip should instrument the
loss distribution, such that the performance of Reno style
bulk transport can be estimated.
BTC algorithms that can trigger fast retransmits earlier than
following three duplicate acknowledgments (e.g. at small
window [LowWindow]), should instrument and fully document
these events as well.
3.2.4 False timeouts
All false timeouts, (where the transmission timer expires before
the ACK for some previously transmitted data arrives) should be
instrumented when possible. Note that depending upon how the BTC
metric implements sequence numbers, this may be difficult to
detect.
3.3 Ancillary metrics relating to flow based path properties
All BTC metrics provide unique vantage points for instrumenting
certain path properties relating to closely spaced packets. As in
the case of RTT duration outages, these can be impossible to
diagnose at low rates (less than 1 packet per RTT) and
inappropriate to test at rates above the BTC.
All BTC metrics should instrument packet reordering. The severity
of the reordering can be classified as one of three different
cases, each of which should be instrumented.
Packets that are only slightly out of order should not trigger
retransmission, but they may affect the window calculation.
BTC metrics must document how slightly out-of-order packets
affect the congestion window calculation. The frequency and
distance out of sequence must be instrumented for all
out-of-order packets.
If packets are sufficiently out-of-order, the Fast Retransmit
algorithm will be invoked in advance of the delayed packet's
late arrival. These events must be instrumented.
Even though the the late arriving packet will complete
recovery, the the window must still be reduced by half.
Under some rare conditions packets have been observed that are
far out of order - sometimes many seconds late [Pax97b].
These should always be instrumented.
The BTC should instrument the maximum cwnd observed during
congestion avoidance and slow start. A TCP running over the same
path must have sufficient sender buffer space and receiver window
(and window shift [RFC1323]) to cover this cwnd.
There are several other path properties that one might measure
within a BTC metric. For example, with an embedded one-way delay
metric it may be possible to measure how queueing delay and
and (RED) drop probabilities are correlated to window size.
These are all open research questions.
3.4 Ancillary metrics pertaining to MTU discovery
Under some conditions, BTC can be very sensitive to segment size.
In addition to instrumenting the segment size, a BTC metric should
indicate how it was selected: by path MTU discovery [RFC1191], a
manual control, system default, or the maximum MTU for the
interface.
Note that the most popular LAN technologies have smaller MTUs
than nearly all WAN technologies. As a consequence, it is
difficult to measure the true performance of a wide area path
without subjecting it to the smaller MTU of the LAN.
3.4 Ancillary metrics as calibration checks
Unlike low rate metrics, BTC must have explicit checks that the
test platform is not the bottleneck, either due to insufficient
tester data rate or buffer space.
Ideally all queues within the tester should be instrumented. All
packets dropped within the tester should be instrumented as tester
failures, invalidating a measurement.
The maximum queue lengths should be instrumented. Any significant
queue may indicate that the tester itself has insufficient burst
data rate, and is slightly smoothing the data into the network.
3.4.3 Validate Reverse path load
@@@@ What happens to a BTC when the reverse path is congested? Is
this identical to TCP? What should happen? How should it be
instrumented?
#
# Some implementations (mine!) have an annoying feature whereby ACK loss
# looks just like data loss. This should be documented. If ACK loss
# and data loss can be detected separately, I think ACK loss rate should
# be reported, as it slightly changes the ACK clock (can impact
# algorithms like slow start that work on a per ACK basis and can make
# the sender more bursty, which could cause more loss).
@ and mine --MM--
3.5 Ancillary metrics relating to the need for advanced TCP features
If TCP would require RFC1323 features (window scaling, timestamp
based round trip time measurement, protection from wrapped
sequences, etc) to match the BTC performance, it should be
reported.
4 Acknowledgments
Jeff Semke, for numerous clarifications.
5 References
[LowWindow] @@@@@ Current work
[FF96] Fall, K., Floyd, S.. "Simulation-based Comparisons of Tahoe,
Reno and SACK TCP". Computer Communication Review, July 1996.
ftp://ftp.ee.lbl.gov/papers/sacks.ps.Z.
[FH98] Floyd, S., Henderson, T., "The NewReno Modification to
TCP's Fast Recovery Algorithm", Work in progress
draft-ietf-tcpimpl-newreno-00.txt
[Flo95] Floyd, S., "TCP and successive fast retransmits",
March 1995, Obtain via ftp://ftp.ee.lbl.gov/papers/fastretrans.ps.
[RF98] K. Ramakrishnan, S. Floyd, "A Proposal to add Explicit
Congestion Notification (ECN) to IP", Work in progress
draft-kksjf-ecn-03.txt
[Hoe96] Hoe, J., "Improving the start-up behavior of a congestion
control scheme for TCP, Proceedings of ACM SIGCOMM '96,
August 1996.
[Hoe95] Hoe, J., "Startup dynamics of TCP's congestion control
and avoidance schemes". Master's thesis, Massachusetts Institute
of Technology, June 1995.
[Jac88] Jacobson, V., "Congestion Avoidance and Control",
Proceedings of SIGCOMM '88, Stanford, CA., August 1988.
[Lak94] Lakshman, Effects of random loss
[MM96a] Mathis, M. and Mahdavi, J. "Forward acknowledgment:
Refining TCP congestion control", Proceedings of ACM SIGCOMM '96,
Stanford, CA., August 1996.
[MM96b] M. Mathis, J. Mahdavi, "TCP Rate-Halving with Bounding
Parameters" Available from
http://www.psc.edu/networking/papers/FACKnotes/current.
[MSMO97] Mathis, M., Semke, J., Mahdavi, J., Ott, T.,
"The Macroscopic Behavior of the TCP Congestion Avoidance
Algorithm", Computer Communications Review, 27(3), July 1997.
[OKM96a], Ott, T., Kemperman, J., Mathis, M., "The Stationary
Behavior of Ideal TCP Congestion Avoidance", In progress, August
1996. Obtain via pub/tjo/TCPwindow.ps using anonymous ftp to
ftp.bellcore.com
[OKM96b], Ott, T., Kemperman, J., Mathis, M., "Window Size
Behavior in TCP/IP with Constant Loss Probability", DIMACS
Special Year on Networks, Workshop on Performance of Real-Time
Applications on the Internet, Nov 1996.
[Pax97a] Paxson, V., "Automated Packet Trace Analysis of TCP
Implementations", Proceedings of ACM SIGCOMM '97, August 1997.
[Pax97b] Paxson, V., "End-to-End Internet Packet Dynamics,"
Proceedings of SIGCOMM '97, Cannes, France, Sep. 1997.
[Pax97c] Paxson, V, editor "Known TCP Implementation Problems",
Work in progress: http://reality.sgi.com/sca/tcp-impl/prob-01.txt
[PFTK98] Padhye, J., Firoiu. V., Towsley, D., and Kurose, J., "TCP
Throughput: A Simple Model and its Empirical Validation",
Proceedings of ACM SIGCOMM '98, August 1998.
[RFC1191] Mogul, J., Deering, S., "Path MTU Discovery",
November 1990, Obtain via:
ftp://ds.internic.net/rfc/rfc1191.txt
[RFC1323] Jacobson, V., Braden, R., Borman, D., "TCP Extensions
for High Performance", May 1992, Obtain via:
ftp://ds.internic.net/rfc/rfc1323.txt
[RFC2001] Stevens, W., "TCP Slow Start, Congestion Avoidance,
Fast Retransmit, and Fast Recovery Algorithms",
ftp://ds.internic.net/rfc/rfc2001.txt
[RFC2001.bis] Allman, M., Paxson, V., Stevens, W., "TCP Congestion
Control". Work in progress draft-ietf-cong-control-01.txt, to
update RFC2001.
[RFC2018] Mathis, M., Mahdavi, J. Floyd, S., Romanow, A., "TCP
Selective Acknowledgment Options", 1996, Obtain via:
ftp://ds.internic.net/rfc/rfc2018.txt
[RFC2330] Paxson, V., Almes, G., Mahdavi, J., Mathis, M.,
"Framework for IP Performance Metrics" , 1998, Obtain via:
ftp://ds.internic.net/rfc/rfc2330.txt
[Ste94] Stevens, W., "TCP/IP Illustrated, Volume 1: The
Protocols", Addison-Wesley, 1994.
Author's Addresses
Matt Mathis
Pittsburgh Supercomputing Center
4400 Fifth Ave.
Pittsburgh PA 15213
mathis@psc.edu
http://www.psc.edu/~mathis
Mark Allman
NASA Lewis Research Center/Sterling Software
21000 Brookpark Rd. MS 54-2
Cleveland, OH 44135
216-433-6586
mallman@lerc.nasa.gov
http://gigahertz.lerc.nasa.gov/~mallman
Datatracker
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