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Versions: 00 01 02 03 04 05 rfc3148                                     
  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 >

  Status of this Document

   This document is an Internet-Draft.  Internet-Drafts are working
   documents of the Internet Engineering Task Force (IETF), its areas,
   and its working groups.  Note that other groups may also distribute
   working documents as Internet-Drafts.

   Internet-Drafts are draft documents valid for a maximum of six
   months, and may be updated, replaced, or obsoleted by other documents
   at any time.  It is inappropriate to use Internet-Drafts as reference
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   To view the entire list of current Internet-Drafts, please check the
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   Rim), ftp.ietf.org (US East Coast), or ftp.isi.edu (US West Coast).

   This memo provides information for the Internet community.  This memo
   does not specify an Internet standard of any kind.  Distribution of
   this memo is unlimited.

  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