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Differences from draft-ietf-ippm-btc-framework-03.txt
INTERNET-DRAFT Expires May 2001 INTERNET-DRAFT
Network Working Group Matt Mathis
INTERNET-DRAFT Pittsburgh Supercomputing Center
Expiration Date: May 2001 Mark Allman
NASA Glenn/BBN
December, 2000
A Framework for Defining Empirical Bulk Transfer Capacity Metrics
< draft-ietf-ippm-btc-framework-04.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
other groups may also distribute working documents as
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Internet-Drafts are draft documents valid for a maximum of six
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at any time. It is inappropriate to use Internet-Drafts as
reference material or to cite them other than as ``work in
progress.''
The list of current Internet-Drafts can be accessed at
http://www.ietf.org/ietf/1id-abstracts.txt
The list of Internet-Draft Shadow Directories can be accessed at
http://www.ietf.org/shadow.html.
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'' bytes transfered
(i.e., not including header bytes or emulated header bytes). Also
note that the amount of data sent should only include the unique
number of bytes 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].
* [RFC2581] does not specify which cwnd increase algorithm (slow
start or congestion avoidance) should be used when cwnd equals
ssthresh.
* [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 2.3).
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 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
The framework for specifying BTC metrics outlined in this document
does not pose any threat to Internet security. The BTC metrics
defined based on this specification will be as ``network friendly''
as current TCP connections.
5 Acknowledgments
Thanks to Jeff Semke for numerous clarifications.
6 References
[ABF00] Mark Allman, Hari Balakrishnan, Sally Floyd. Enhancing
TCP's Loss Recovery Using Limited Transmit, August
2000. Internet-Draft draft-ietf-tsvwg-limited-xmit-00.txt (work
in progress).
[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: ftp://ds.internic.net/rfc/rfc793.txt
[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
[RFC1633] Braden R., Clark D., Shenker S., "Integrated Services in
the Internet Architecture: an Overview"., 1994.
[RFC2001] Stevens, W., "TCP Slow Start, Congestion Avoidance, Fast
Retransmit, and Fast Recovery Algorithms", 1997, Obtain via:
ftp://ds.internic.net/rfc/rfc2001.txt
[RFC2018] Mathis, M., Mahdavi, J. Floyd, S., Romanow, A., "TCP
Selective Acknowledgment Options", 1996, Obtain via:
ftp://ds.internic.net/rfc/rfc2018.txt
[RFC2119] Bradner, S., "Key words for use in RFCs to Indicate
Requirement Levels", 1997, Obtain via:
ftp://ds.internic.net/rfc/rfc2119.txt
[RFC2216] Shenker, S., Wroclawski, J., "Network Element Service
Specification Template", 1997, Obtain via:
ftp://ds.internic.net/rfc/rfc2216.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
[RFC2475] Black D., Blake S., Carlson M., Davies E., Wang Z., Weiss
W., "An Architecture for Differentiated Services"., 1998.
[RFC2481] K. Ramakrishnan, S. Floyd, "A Proposal to add Explicit
Congestion Notification (ECN) to IP", 1999, Obtain via:
ftp://ds.internic.net/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:
ftp://ds.internic.net/rfc/rfc2525.txt
[RFC2581] Allman, M., Paxson, V., Stevens, W., "TCP Congestion
Control"., 1999, Obtain via:
ftp://ds.internic.net/rfc/rfc2581.txt
[RFC2582] Floyd, S., Henderson, T., "The NewReno Modification to
TCP's Fast Recovery Algorithm", 1999, Obtain via:
ftp://ds.internic.net/rfc/rfc2582.txt
[RFC2988] Paxson, V., Allman, M., "Computing TCP's Retransmission
Timer", November 2000, Obtain via:
ftp://ds.internic.net/rfc/rfc2988.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
NASA Glenn Research Center/BBN Technologies
Lewis Field
21000 Brookpark Rd. MS 54-2
Cleveland, OH 44135
216-433-6586
mallman@grc.nasa.gov
http://roland.grc.nasa.gov/~mallman
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