A Framework for Defining Empirical Bulk Transfer Capacity Metrics
RFC 3148
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RFC - Informational
(July 2001; No errata)
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Matt Mathis
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Mark Allman
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2013-03-02
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RFC 3148 (Informational)
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Network Working Group M. Mathis
Request for Comments: 3148 Pittsburgh Supercomputing Center
Category: Informational M. Allman
BBN/NASA Glenn
July 2001
A Framework for Defining Empirical Bulk Transfer Capacity Metrics
Status of this Memo
This memo provides information for the Internet community. It does
not specify an Internet standard of any kind. Distribution of this
memo is unlimited.
Copyright Notice
Copyright (C) The Internet Society (2001). All Rights Reserved.
Abstract
This document defines a framework for standardizing multiple BTC
(Bulk Transport Capacity) metrics that parallel the permitted
transport diversity.
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). 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.
Two approaches are used. First, each BTC metric must be much more
tightly specified than the typical IETF protocol. Second, each BTC
methodology is expected to collect some ancillary metrics which are
potentially useful to support analytical models of BTC.
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
Mathis, et al. Informational [Page 1]
RFC 3148 Framework for Defining Empirical BTC Metrics July 2001
[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].
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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. 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.
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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.
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* 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).
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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.
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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.
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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 queuing 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.
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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.
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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.
Matt Mathis's work was supported by the National Science Foundation
under Grant Numbers 9415552 and 9870758.
Mathis, et al. Informational [Page 10]
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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] V. T. Lakshman and U. Madhow. The Performance of TCP/IP
for Networks with High Bandwidth-Delay Products and
Random Loss. IFIP Transactions C-26, High Performance
Networking, pages 135--150, 1994.
[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.
Mathis, et al. Informational [Page 11]
RFC 3148 Framework for Defining Empirical BTC Metrics July 2001
[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, 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.
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[RFC793] Postel, J., "Transmission Control Protocol", STD 7, RFC
793, September 1981. Obtain via: http://www.rfc-
editor.org/rfc/rfc793.txt
[RFC1191] Mogul, J. and S. Deering, "Path MTU Discovery", RFC
1191, November 1990. Obtain via: http://www.rfc-
editor.org/rfc/rfc1191.txt
[RFC1323] Jacobson, V., Braden, R. and D. Borman, "TCP Extensions
for High Performance", May 1992. Obtain via:
http://www.rfc-editor.org/rfc/rfc1323.txt
[RFC1633] Braden R., Clark D. and S. Shenker, "Integrated Services
in the Internet Architecture: an Overview", RFC 1633,
June 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", RFC 2001,
January 1997. Obtain via: http://www.rfc-
editor.org/rfc/rfc2001.txt
[RFC2018] Mathis, M., Mahdavi, J. Floyd, S., Romanow, A., "TCP
Selective Acknowledgment Options", RFC 2018, October
1996. Obtain via: http://www.rfc-
editor.org/rfc/rfc2018.txt
[RFC2119] Bradner, S., "Key words for use in RFCs to Indicate
Requirement Levels", BCP 14, RFC 2119, March 1997.
Obtain via: http://www.rfc-editor.org/rfc/rfc2119.txt
[RFC2216] Shenker, S. and J. Wroclawski, "Network Element Service
Specification Template", RFC 2216, September 1997.
Obtain via: http://www.rfc-editor.org/rfc/rfc2216.txt
[RFC2330] Paxson, V., Almes, G., Mahdavi, J. and M. Mathis,
"Framework for IP Performance Metrics", RFC 2330, April
1998. Obtain via: http://www.rfc-
editor.org/rfc/rfc2330.txt
[RFC2475] Black D., Blake S., Carlson M., Davies E., Wang Z. and
W. Weiss, "An Architecture for Differentiated Services",
RFC 2475, December 1998. Obtain via: http://www.rfc-
editor.org/rfc/rfc2475.txt
Mathis, et al. Informational [Page 13]
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[RFC2481] Ramakrishnan, K. and S. Floyd, "A Proposal to add
Explicit Congestion Notification (ECN) to IP", RFC 2481,
January 1999. Obtain via: http://www.rfc-
editor.org/rfc/rfc2481.txt
[RFC2525] Paxson, V., Allman, M., Dawson, S., Fenner, W., Griner,
J., Heavens, I., Lahey, K., Semke, J. and B. Volz,
"Known TCP Implementation Problems", RFC 2525, March
1999. Obtain via: http://www.rfc-
editor.org/rfc/rfc2525.txt
[RFC2581] Allman, M., Paxson, V. and W. Stevens, "TCP Congestion
Control", RFC 2581, April 1999. Obtain via:
http://www.rfc-editor.org/rfc/rfc2581.txt
[RFC2582] Floyd, S. and T. Henderson, "The NewReno Modification to
TCP's Fast Recovery Algorithm", RFC 2582, April 1999.
Obtain via: http://www.rfc-editor.org/rfc/rfc2582.txt
[RFC2988] Paxson, V. and M. Allman, "Computing TCP's
Retransmission Timer", RFC 2988, November 2000. Obtain
via: http://www.rfc-editor.org/rfc/rfc2988.txt
[RFC3042] Allman, M., Balakrishnan, H. and S. Floyd, "Enhancing
TCP's Loss Recovery Using Limited Transmit", RFC 3042,
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.
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RFC 3148 Framework for Defining Empirical BTC Metrics July 2001
Author's Addresses
Matt Mathis
Pittsburgh Supercomputing Center
4400 Fifth Ave.
Pittsburgh PA 15213
EMail: 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
Phone: 216-433-6586
EMail: mallman@bbn.com
http://roland.grc.nasa.gov/~mallman
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Full Copyright Statement
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