INTERNET-DRAFT          Expires Jan. 2000            INTERNET-DRAFT

  Network Working Group                                   Matt Mathis
  INTERNET-DRAFT                     Pittsburgh Supercomputing Center
  Expiration Date: Jan. 2000                              Mark Allman
                                                           NASA Glenn
                                                           June, 1999

                  Empirical Bulk Transfer Capacity

              < draft-ietf-ippm-btc-framework-01.txt >

Status of this Document

    This document is an Internet-Draft and is in full conformance with
    all provisions of Section 10 of RFC2026.

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    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 to run 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

    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.

    [RFC2581] 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.

    There is also evidence that most TCP implementations exhibit
    non-linear performance over some portion of their operating region.
    It is possible to construct simple simulation examples where
    incremental improvements to a path (such as raising the link
    data rate) results in lower overall TCP throughput [MathisIPPM1998?].

    We beleive that such non-linearity reflects weakness in our current
    understanding of congestion control and is present to some extent in
    all TCP implementations and BTC metrics.  Note that such
    non-linearity (in either TCP or a BTC metric) is potentially
    problematic in the market because investment in capacity might
    actually reduce the preceived quality of the network.   Ongoing
    research in congestion dynamics has some hope of mitigating or
    modeling the these non-linearities.

    Furthermore related areas, including Integrated services[@@],
    differentiated services[@@] and Internet traffic analysis[@@] are
    all currently receiving significant attention from the research
    community.  It is likely that we will see new experimental
    congestion control algorithms in the near future.  In addition,
    Explicit Congestion Notification (ECN) [RFC2481] 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 transport 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.  If a BTC methodology does not collect these
    ancillary metrics, it should collect enough information such that
    these metrics can be derived (for instance a segment trace file).

    For example, the models in [PFTK98, MSMO97, OKM96a, Lak94] all
    predict bulk transfer performance based on path properties such as
    loss rate and round trip time.  A BTC methodology that 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 the ancillary metrics are expected to be useful for
    resolving disparity between different BTC methodologies.  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.

    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

    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 utilize the congestion
    control algorithms published in [Jac88] and further refined in
    [RFC2581].  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
    [RFC2581] (which the reader is assumed to be familiar with).
    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 cwnd by a constant multiplicative fraction
    on congestion, as indicated by lost segments or Explicit Congestion
    Notification messages [RFC2481].  The window closes by half the
    number of outstanding data segments in flight when loss is detected.
    A BTC metric must specify the following Congestion Avoidance

        The exact algorithm for incrementing cwnd in TCP is left to the
        implementer.  Several candidate algorithms are outlined in
        [RFC2581].  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.

        [RFC2581] permits, but does not require, an extra plus one
        segment cwnd adjustment following the multiplicative decrease of
        cwnd.  This is because [RFC2581] 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) expires.  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 BTC of the path.  Calculating the RTO is subject to
    a number of details that are not standardized (however, [WS95]
    outlines a popular implementation).  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 increase the congestion window for new or recently restarted
    connections up to an appropriate level for the network path.  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 [RFC2581].  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 [RFC2581].  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 [RFC2581].

    In Reno TCP, Fast Retransmit and Fast Recovery are used to support
    the Congestion Avoidance algorithm during loss recovery.  During
    Fast Recovery, the data receiver sends duplicated acknowledgments,
    per the TCP specification [RFC793].  The data sender uses these
    duplicate ACKs to detect loss, to estimate the quantity of
    outstanding data in the network and to clock out new data in an
    effort to keep the ACK clock running.

    The Fast Retransmit/Fast Recovery algorithms should be implemented
    in all BTC methodologies as specified in [RFC2581].

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 the network path have a large effect on performance [MM96a].
    Additional simulations have shown that under some conditions,
    slightly better networks (higher bandwidth, lower delay or less
    competing traffic) yield lower throughput [MathisIPPMDec1998?].

    [RFC2581] allows a TCP implementation to use more robust loss
    recovery algorithms, such as NewReno [RFC2582,FF96,Hoe96] and
    SACK-based algorithms [FF96,MM96a,MM96b].  While allowing these
    algorithms, [RFC2581] does not define any such algorithm and
    therefore, a BTC metric that implements advanced loss recovery
    algorithms must fully specify the details.

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 (if known).

3 Ancillary Metrics

    The following ancillary metrics can provide additional information
    about the network and the behavior of the implemented congestion
    control algorithm in response to the behavior of the network path.
    It is recommended that these metrics be built into each BTC
    methodology.  Alternatively, the BTC implementation should provide
    enough information such that the ancillary metrics can be derived
    via post-processing (e.g., by providing a segment trace of the

3.1 Congestion Avoidance Capacity

    The "Congestion Avoidance Capacity" (CAC) metric is 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 periods (except the single segment Slow-Start
    that is permitted to follow recovery, as discussed in section 2.3).

    In principle a CAC metric would be an ideal BTC metric, as it
    captures what should be TCP's steady state behavior.  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.  It has been
    found that timeouts and periods of slow start loss recovery are
    prevalent in traffic on the Internet [LK98] and therefore these
    should be included in the BTC metric.

    When TCP looses Self-Clock it is reestablished through a
    retransmission timeout and Slow-Start.  These algorithms nearly
    always require 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 safely transmit data.  That is, if TCP
    experiences a timeout after losing a 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 the transmission of
    new data.  Recent research in congestion control (e.g., FACK
    [MM96a], NewReno [FF96,RFC2582]) 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 Preservation of Self-Clock

    Losing the ACK clock can have a large effect on the overall BTC, and
    the clock is itself fragile in ways that are dependent on the loss
    recovery algorithm.  Therefore, it is important that the transition
    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 an
    alternate congestion control algorithm would have successfully
    preserved the Self-Clock.  In this event, instrumenting key parts of
    the BTC state (such as the congestion window) 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

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

    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.

    Note that there are some conditions, such as when operating with a
    very small window, in which there is a significant probability that
    an entire window can be 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.

3.2.4  False Timeouts

    All false timeouts, (where the retransmission 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 frequency
    and distance out of sequence must be instrumented for all
    out-of-order packets.  The severity of the reordering can be
    classified as one of three different cases, each of which should be

        Packets that are only slightly out of order should not trigger
        retransmission (via fast retransmit), but they may affect the
        window calculation.  BTC metrics must document how slightly
        out-of-order packets affect the congestion window calculation.

        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 will 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 as the BTC 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
    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 configuration, system default, or the maximum MTU for the

    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.

    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
# 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 advanced TCP extensions to match BTC
    performance (such as RFC 1323 or RFC 2018 features), it should be

4 Acknowledgments

    Thanks to Jeff Semke for numerous clarifications.

5  References

    [FF96] Fall, K., Floyd, S..  "Simulation-based Comparisons of Tahoe,
        Reno and SACK TCP".  Computer Communication Review, July 1996.

    [Flo95] Floyd, S., "TCP and successive fast retransmits", March
        1995, Obtain via

    [Hoe96] Hoe, J., "Improving the start-up behavior of a congestion
        control scheme for TCP, Proceedings of ACM SIGCOMM '96, August

    [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

    [LK98] Lin, D. and Kung, H.T., "TCP Fast Recovery Strategies:
        Analysis and Improvements", Proceedings of InfoCom, March 1998.

    [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

    [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/ using anonymous ftp to

    [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.

    [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.

    [RFC793] Postel, J., "Transmission Control Protocol", 1981, Obtain

    [RFC1191] Mogul, J., Deering, S., "Path MTU Discovery", November
        1990, Obtain via:

    [RFC1323] Jacobson, V., Braden, R., Borman, D., "TCP Extensions for
        High Performance", May 1992, Obtain via:

    [RFC2001] Stevens, W., "TCP Slow Start, Congestion Avoidance, Fast
        Retransmit, and Fast Recovery Algorithms", 1997, Obtain via:

    [RFC2018] Mathis, M., Mahdavi, J. Floyd, S., Romanow, A., "TCP
        Selective Acknowledgment Options", 1996, Obtain via:

    [RFC2330] Paxson, V., Almes, G., Mahdavi, J., Mathis, M., "Framework
        for IP Performance Metrics" , 1998, Obtain via:

    [RFC2481] K. Ramakrishnan, S. Floyd, "A Proposal to add Explicit
        Congestion Notification (ECN) to IP", 1999, Obtain via:

    [RFC2525] V. Paxson, M. Allman, S. Dawson, W. Fenner, J. Griner,
        I. Heavens, K. Lahey, J. Semke, B. Volz, "Known TCP
        Implementation Problems", 1999, Obtain via:

    [RFC2581] Allman, M., Paxson, V., Stevens, W., "TCP Congestion
        Control"., 1999, Obtain via:

    [RFC2582] Floyd, S., Henderson, T., "The NewReno Modification to
        TCP's Fast Recovery Algorithm", 1999, Obtain via:

    [Ste94] Stevens, W., "TCP/IP Illustrated, Volume 1: The Protocols",
        Addison-Wesley, 1994.

    [WS95] Wright, G., Stevens, W., "TCP/IP Illustrated Volume II: The
        Implementation", Addison-Wesley, 1995.

Author's Addresses

    Matt Mathis
    Pittsburgh Supercomputing Center
    4400 Fifth Ave.
    Pittsburgh PA 15213

    Mark Allman
    NASA Glenn Research Center/GTE Internetworking
    Lewis Field
    21000 Brookpark Rd.  MS 54-2
    Cleveland, OH  44135