INTERNET-DRAFT          Expires May 2001             INTERNET-DRAFT

  Network Working Group                                   Matt Mathis
  INTERNET-DRAFT                     Pittsburgh Supercomputing Center
  Expiration Date: May 2001                               Mark Allman
                                                       BBN/NASA Glenn
                                                       February, 2001


   A Framework for Defining Empirical Bulk Transfer Capacity Metrics

              < draft-ietf-ippm-btc-framework-05.txt >

Status of this Document

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

    Internet-Drafts are working documents of the Internet Engineering
    Task Force (IETF), its areas, and its working groups.  Note that
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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

    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].  Although
    [RFC2119] was written with protocols in mind, the key words are used
    in this document for similar reasons.  They are used to ensure that
    each BTC methodology defined contains specific pieces of
    information.

    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
    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.  The specific definition
    of the bulk transfer capacity that MUST be reported by a BTC tool is:

        BTC = data_sent / elapsed_time

    where ``data_sent'' represents the unique ``data'' bits transfered
    (i.e., not including header bits or emulated header bits).  Also
    note that the amount of data sent should only include the unique
    number of bits transmitted (i.e., if a particular packet is
    retransmitted the data it contains should be counted only once).

    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 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 congestion control 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 (or BTC) [Mat98].

    We believe 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 perceived quality of the network.  Ongoing
    research in congestion dynamics has some hope of mitigating or
    modeling the these non-linearities.

    Related areas, including integrated services
    [RFC1633,RFC2216], differentiated services [RFC2475] and Internet
    traffic analysis [MSMO97,PFTK98,Pax97b,LM97] 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, and thus the BTC framework and metrics may need
    to be revisited in the future.

    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).

    As an 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
    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 utilize the congestion
    control algorithms published in [Jac88] and further refined in
    [RFC2581].  In addition to using 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 implement slow start and congestion avoidance,
    as specified in [RFC2581] (with extra details also specified, as
    outlined below).  All BTC methodologies SHOULD implement fast
    retransmit and fast recovery as outlined in [RFC2581].  Finally, all
    BTC methodologies MUST implement a retransmission timeout.

    The algorithms specified in [RFC2581] give implementers some choices
    in the details of the implementation.  The following is a list of
    details about the congestion control algorithms that are either
    underspecified in [RFC2581] or very important to define when
    constructing a BTC methodology.  These details MUST be specifically
    defined in each BTC methodology.

      * [RFC2581] does not standardize a specific algorithm for
        increasing cwnd during congestion avoidance.  Several candidate
        algorithms are given in [RFC2581].  The algorithm used in a
        particular BTC methodology MUST be defined.

      * [RFC2581] does not specify which cwnd increase algorithm (slow
        start or congestion avoidance) should be used when cwnd equals
        ssthresh.  This MUST be specified for each BTC methodology.

      * [RFC2581] allows TCPs to use advanced loss recovery mechanism
        such as NewReno [RFC2582,FF96,Hoe96] and SACK-based algorithms
        [FF96,MM96a,MM96b].  If used in a BTC implementation, such an
        algorithm MUST be fully defined.

      * 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.

      * TCP includes a retransmission timeout (RTO) to trigger
        retransmissions of segments that have not been acknowledged
        within an appropriate amount of time and have not been
        retransmitted via some more advanced loss recovery algorithm.  A
        BTC implementation MUST include a retransmission timer.
        Calculating the RTO is subject to a number of details that MUST
        be defined for each BTC metric.  In addition, a BTC metric MUST
        define when the clock is set and the granularity of the clock.

        [RFC2988] specifies the behavior of the retransmission timer.
        However, there are several details left to the implementer which
        MUST be specified for each BTC metric defined.

    Note that as new congestion control algorithms are placed on the
    standards track they may be incorporated into BTC metrics (e.g., the
    Limited Transmit algorithm [ABF00]).  However, any implementation
    decisions provided by the relevant RFCs SHOULD be fully specified in
    the particular BTC metric.

3   Ancillary Metrics

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

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).

    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 chosen.  It has been
    found that timeouts and periods of slow start loss recovery are
    prevalent in traffic on the Internet [LK98,BPS+97] and therefore these
    should be captured by the BTC metric.

    When TCP loses Self-Clock it is re-established 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
    likely 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], rate-halving [MSML99]) can be
    characterized as making TCP's Self-Clock more tenacious, while
    preserving fairness under adverse conditions.  This work is
    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, the transition between timer driven
    and Self-Clocked operation SHOULD 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 transmission, the possibility exists that an
    alternate congestion control algorithm would have successfully
    preserved the Self-Clock.  A BTC SHOULD instrument key items in the
    BTC state (such as the congestion window) in the hopes that this 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 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 (again
    highlighting the importance of instrumenting cwnd).

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 (as
    discussed in section 2).

    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 alternate congestion
    control algorithms may be estimated (e.g., Reno style).

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 observing 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 of the network path.

    All BTC metrics SHOULD instrument packet reordering.  The frequency
    and distance out-of-sequence SHOULD 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
    reported.

        Segments that are only slightly out-of-order should not trigger
        the fast retransmit algorithm, but they may affect the window
        calculation.  BTC metrics SHOULD document how slightly
        out-of-order segments affect the congestion window calculation.

        If segments are sufficiently out-of-order, the Fast Retransmit
        algorithm will be invoked in advance of the delayed packet's
        late arrival.  These events SHOULD 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 segments have been observed that are
        far out of order - sometimes many seconds late [Pax97b].  These
        SHOULD always be instrumented.

    BTC implementations SHOULD instrument the maximum cwnd observed
    during congestion avoidance and slow start.  A TCP running over the
    same path as the BTC metric must have sufficient sender buffer space
    and receiver window (and window shift [RFC1323]) to cover this cwnd
    in order to expect the same performance.

    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 as Calibration Checks

    Unlike low rate metrics, BTC SHOULD include explicit checks that the
    test platform is not the bottleneck.

    Any detected dropped packets within the sending host MUST be reported.
    Unless the sending interface is the path bottleneck, any dropped
    packets probably indicates a measurement failure.

    The maximum queue lengths within the sending host SHOULD be
    instrumented.  Any significant queue may indicate that the sending
    host has insufficient burst data rate, and is smoothing the data
    being transmitted into the network.

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
    reported.

3.6 Validate Reverse Path Load

    To the extent possible, the BTC metric SHOULD distinguish between
    the properties of the forward and reverse paths.

    BTC methodologies which rely on non-cooperating receivers may only
    be able to measure round trip path properties and may not be able to
    independently differentiate between the properties of the forward
    and reverse paths.  In this case the load on the reverse path
    contributed by the BTC metric SHOULD be instrumented (or computed)
    to permit other means of gauge the proportion of the round trip path
    properties attributed to the the forward and reverse paths.

    To the extent possible, BTC methodologies that rely on cooperating
    receivers SHOULD support separate ancillary metrics for the forward
    and reverse paths.

4   Security Considerations

    Conducting Internet measurements raises security concerns.  This
    memo does not specify a particular implementation of a metric, so it
    does not directly affect the security of the Internet nor of
    applications which run on the Internet.  However, metrics produced
    within this framework, and in particular implementations of the
    metrics may create security issues.

4.1 Denial of Service Attacks

    Bulk Transport Capacity metrics, as defined in this document,
    naturally attempt to fill a bottleneck link.  The BTC metrics based
    on this specification will be as ``network friendly'' as current
    well-tuned TCP connections.  However, since the ``connection'' may
    not be using TCP packets, a BTC test may appear to network operators
    as a denial of service attack.

    Administrators of the source host of a test, the destination host of
    a test, and the intervening network(s) may wish to establish
    bilateral or multi-lateral agreements regarding the timing, size,
    and frequency of collection of BTC metrics.

4.2 User data confidentiality

    Metrics within this framework generate packets for a sample, rather
    than taking samples based on user data.  Thus, a BTC metric does not
    threaten user data confidentiality.

4.3 Interference with metrics

    It may be possible to identify that a certain packet or stream of
    packets are part of a BTC metric.  With that knowledge at the
    destination and/or the intervening networks, it is possible to
    change the processing of the packets (e.g. increasing or decreasing
    delay, introducing or heroically preventing loss) that may distort
    the measured performance.  It may also be possible to generate
    additional packets that appear to be part of a BTC metric. These
    additional packets are likely to perturb the results of the sample
    measurement.

    To discourage the kind of interference mentioned above, packet
    interference checks, such as cryptographic hash, may be used.

5   IANA Considerations

    Since this metric framework does not define a specific
    protocol, nor does it define any well-known values, there
    are no IANA considerations for this document.   However,
    a bulk transport capacity metric within this framework,
    and in particular protocols that implement a metric may have
    IANA considerations that need to be addressed.

6   Acknowledgments

    Thanks to Wil Leland, Jeff Semke, Matt Zekauskas and the IPPM
    working group for numerous clarifications.

7   References

    [BPS+97] Hari Balakrishnan, Venkata Padmanabhan, Srinivasan Seshan,
        Mark Stemm, and Randy Katz.  TCP Behavior of a Busy Web Server:
        Analysis and Improvements.  Technical Report UCB/CSD-97-966,
        August 1997.  Available from
        http://nms.lcs.mit.edu/~hari/papers/csd-97-966.ps.  (Also in
        Proc. IEEE INFOCOM Conf., San Francisco, CA, March 1998.)

    [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.

    [Flo95] Floyd, S., "TCP and successive fast retransmits", March
        1995, Obtain via ftp://ftp.ee.lbl.gov/papers/fastretrans.ps.

    [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

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

    [LM97] T.V.Lakshman and U.Madhow.  "The Performance of TCP/IP for
        Networks with High Bandwidth-Delay Products and Random Loss".
        IEEE/ACM Transactions on Networking, Vol. 5, No. 3, June 1997,
        pp.336-350.

    [Mat98] Mathis, M., "Empirical Bulk Transfer Capacity", IP
        Performance Metrics Working Group report in Proceedings of the
        Forty Third Internet Engineering Task Force, Orlando, FL,
        December 1988.  Available from
        http://www.ietf.org/proceedings/98dec/43rd-ietf-98dec-122.html
        and
        http://www.ietf.org/proceedings/98dec/slides/ippm-mathis-98dec.pdf.

    [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.

    [MSML99] Mathis, M., Semke, J., Mahdavi, J., Lahey, K., "The
        Rate-Halving Algorithm for TCP Congestion Control", June 1999.
        Internet-Draft draft-mathis-tcp-ratehalving-00.txt (work in
        progress).

    [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.

    [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
        via: http://www.rfc-editor.org/rfc/rfc793.txt

    [RFC1191] Mogul, J., Deering, S., "Path MTU Discovery", November
        1990, Obtain via: http://www.rfc-editor.org/rfc/rfc1191.txt

    [RFC1323] Jacobson, V., Braden, R., Borman, D., "TCP Extensions for
        High Performance", May 1992, Obtain via:
        http://www.rfc-editor.org/rfc/rfc1323.txt

    [RFC1633] Braden R., Clark D., Shenker S., "Integrated Services in
        the Internet Architecture: an Overview", 1994, Obtain via:
        http://www.rfc-editor.org/rfc/rfc1633.txt

    [RFC2001] Stevens, W., "TCP Slow Start, Congestion Avoidance, Fast
        Retransmit, and Fast Recovery Algorithms", 1997, Obtain via:
        http://www.rfc-editor.org/rfc/rfc2001.txt

    [RFC2018] Mathis, M., Mahdavi, J. Floyd, S., Romanow, A., "TCP
        Selective Acknowledgment Options", 1996, Obtain via:
        http://www.rfc-editor.org/rfc/rfc2018.txt

    [RFC2119] Bradner, S., "Key words for use in RFCs to Indicate
        Requirement Levels", 1997, Obtain via:
        http://www.rfc-editor.org/rfc/rfc2119.txt

    [RFC2216] Shenker, S., Wroclawski, J., "Network Element Service
        Specification Template", 1997, Obtain via:
        http://www.rfc-editor.org/rfc/rfc2216.txt

    [RFC2330] Paxson, V., Almes, G., Mahdavi, J., Mathis, M., "Framework
        for IP Performance Metrics" , 1998, Obtain via:
        http://www.rfc-editor.org/rfc/rfc2330.txt

    [RFC2475] Black D., Blake S., Carlson M., Davies E., Wang Z., Weiss
        W., "An Architecture for Differentiated Services", 1998, Obtain
        via: http://www.rfc-editor.org/rfc/rfc2475.txt

    [RFC2481] K. Ramakrishnan, S. Floyd, "A Proposal to add Explicit
        Congestion Notification (ECN) to IP", 1999, Obtain via:
        http://www.rfc-editor.org/rfc/rfc2481.txt

    [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:
        http://www.rfc-editor.org/rfc/rfc2525.txt

    [RFC2581] Allman, M., Paxson, V., Stevens, W., "TCP Congestion
        Control"., 1999, Obtain via:
        http://www.rfc-editor.org/rfc/rfc2581.txt

    [RFC2582] Floyd, S., Henderson, T., "The NewReno Modification to
        TCP's Fast Recovery Algorithm", 1999, Obtain via:
        http://www.rfc-editor.org/rfc/rfc2582.txt

    [RFC2988] Paxson, V., Allman, M., "Computing TCP's Retransmission
        Timer", November 2000, Obtain via:
        http://www.rfc-editor.org/rfc/rfc2988.txt

    [RFC3042] Allman, M., Balakrishnan, H., Floyd, S., "Enhancing TCP's
        Loss Recovery Using Limited Transmit", January 2001, Obtain via:
        http://www.rfc-editor.org/rfc/rfc3042.txt

    [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
    mathis@psc.edu
    http://www.psc.edu/~mathis

    Mark Allman
    BBN Technologies/NASA Glenn Research Center
    Lewis Field
    21000 Brookpark Rd.  MS 54-2
    Cleveland, OH  44135
    216-433-6586
    mallman@bbn.com
    http://roland.grc.nasa.gov/~mallman