Real Time Flow Measurement Working Group S.W. Handelman
Internet-draft IBM
Hawthorne, NY USA
Nevil Brownlee
U of Auckland, NZ
Greg Ruth
GTE Laboratories, Inc
Waltham, MA USA
S. Stibler
IBM
Hawthorne, NY USA
March 13, 1998
expires
September 13, 1998
RTFM Working Group - New Attributes for Traffic Flow Measurement
<draft-ietf-rtfm-new-traffic-flow-03.txt>
1. Status of this Memo
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2. Introduction
The Real-Time Flow Measurement (RTFM) Working Group (WG) has
developed a system for measuring and reporting information about
traffic flows in the Internet. This document explores the definition
of extensions to the flow measurements as currently defined in [1].
The new attributes described in this document will be useful for
monitoring network performance and will expand the scope of RTFM
beyond simple measurement of traffic volumes. Performance attributes
typically deal with throughput, packet loss, and delays. The WG will
explore the methods by which RTFM can extract values from packets and
flows so as to measure these attributes. The WG will also look at
capturing information on jitter and congestion control. A companion
document to this draft will be written to define the MIB structures
of the new attributes.
This draft was started in 1996 to advance the work of the RTFM group.
The goal of this work is to produce a simple set of abstractions,
which can be easily implemented and at the same time enhance the
value of RTFM Meters. This document also defines a method for
organizing the flow abstractions to augment the existing RTFM flow
table.
Implementations of the RTFM Meter meter have been done by Nevil
Brownlee in the University of Auckland, NZ, and Stephen Stibler and
Sig Handelman at IBM in Hawthorne, NY, USA. The RTFM WG has also
defined the role of the Meter Reader whose role is to retrieve flow
data from the Meter.
2.1 RTFM's Definition of Flows
The RTFM Meter architecture views a flow as a set of packets between
two endpoints (as defined by their source and destination attribute
values and start and end times), and as BI-DIRECTIONAL (i.e. the
meter effectively monitors two sub-flows, one in each direction).
Reasons why RTFM flows are bi-directional:
- The WG is interested in understanding the behavior of sessions
between endpoints.
- The endpoint attribute values (the "Address" and "Type" ones) are
the same for both directions; storing them in bi-directional flows
reduces the meter's memory demands.
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2.2 RTFM's Current Definition of Flows and their Attributes
Flows, as described in the "Architecture" document [1] have the
following properties:
a. They occur between two endpoints, specified as sets of attribute
values in the meter's current rule set. A flow is completely
identified by its set of endpoint attribute values.
b. Each flow may also have values for "computed" attributes (Class
and Kind). These are directly derived from the endpoint attribute
values.
c. A new flow is created when a packet is to be counted that does not
match the attributes of an existing flow. The meter records the time
when this new flow is created.
d. Attribute values in (a), (b) and (c) are set when the meter sees
the first packet for the flow, and are never changed.
e. Each flow has a "LastTime" attribute, which indicates the time the
meter last saw a packet for the flow.
f. Each flow has two packet and two byte counters, one for each flow
direction (Forward and Backward). These are updated as packets for
the flow are observed by the meter.
g. ALL the attributes have (more or less) the same meaning for a
variety of protocols; IPX, AppleTalk, DECnet and CLNS as well as
TCP/IP.
Current flow attributes - as described above - fit very well into the
SNMP data model. They are either static, or are continuously updated
counters. They are NEVER reset. In this document they will be
referred to as "old-style" attributes.
It is easy to add further "old-style" attributes, since they don't
require any new features in the architecture. For example:
- Count of the number of "lost" packets (determined by watching
sequence number fields for packets in each direction; only available
for protocols which have sequence numbers).
- In the future, RTFM could coordinate directly with the Flow Label
from the IPv6 header.
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2.3 RTFM Flows, Integrated Services, IPPM and Research in Flows
The concept of flows has been studied in various different contexts.
For the purpose of extending RTFM, a starting point is the work of
the Integrated Services WG. We will measure quantities that are often
set by Integrated Services configuration programs. We will look at
the work of the Benchmarking / IP Performance Metrics Working Group,
and also look at the work of Claffy, Braun and Polyzos [4]. We will
demonstrate how RTFM can compute throughput, packet loss, and delays
from flows.
An example of the use of capacity and performance information is
found in "The Use of RSVP with IETF Integrated Services" [2]. RSVP's
use of Integrated Services revolves around Token Bucket Rate, Token
Bucket Size, Peak Data Rate, Minimum Policed Unit, Maximum Packet
Size, and the Slack term. These are set by TSpec, ADspec and FLowspec
(Integrated Services Keywords), and are used in configuration and
operation of Integrated Services. RTFM could monitor explicitly Peak
Data Rate, Minimum Policed Unit, Maximum Packet Size, and the Slack
term. RTFM could infer details of the Token Bucket. The WG will
develop measures to work with these service metrics.
RTFM will work with several traffic measurements identified by IPPM
[3]. There are three broad areas in which RTFM is useful for IPPM.
An RTFM Meter could act as a passive device, gathering traffic and
performance statistics at appropriate places in networks (server or
client locations). RTFM could give detailed analyses of IPPM test
flows that pass through the Network segment that RTFM is monitoring.
RTFM could be used to identify the most-used paths in a network mesh,
so that detailed IPPM work could be applied to these most used paths.
3.0 Flow Abstractions
Performance attributes include throughput, packet loss, delays,
jitter, and congestion measures. RTFM will calculate these attributes
in the form of extensions to the RTFM flow attributes according to
three general classes:
o 'packet traces' - collections of attributes of individual packets
in a flow or a segment of a flow.
o 'aggregates' - statistics derived from the flow taken as a whole
(e.g. mean rate, max packet size).
o 'series'- attributes that depend on more than one packet (e.g.
inter-arrival times, short-term traffic rates).
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3.1. Meter Readers and Meters
A note on the relation between Meter Readers and Meters.
As an introduction to flow abstractions one fact must be emphasized.
Several of the measurements enumerated below can be implemented by a
Meter Reader that is tied to the meter with instantaneous response
time and very high bandwidth. If the Meter Reader and Meter can be
arranged in such a way, RTFM could collect Packet Traces with time
stamps and provide them to the Meter Reader for further processing.
A more useful alternative is to have the Meter calculate some flow
statistics locally. This allows a looser coupling between the Meter
and Meter Reader. RTFM will monitor an 'extended attribute' depending
upon settings in its Rule table. RTFM will not create any "extended
attribute" data without explicit instructions in the Rule table.
3.2. Attribute Types
Section 3.0 described three different classes of attributes; this
section considers the "data types" of these attributes.
Packet Traces (as described below) are a special case in that they
are tables with each row containing a sequence of values, each of
varying type. They are essentially 'compound objects' i.e. lists of
attribute values for a string of packets.
Aggregate attributes are like the 'old-style' attributes. The types
are
- Addresses, represented as byte strings (1 to 20 bytes long)
- Counters, represented as 64-bit unsigned integers
- Times, represented as 32-bit unsigned integers
Addresses are saved when the first packet of a flow is observed. They
do not change with time, and they are used as a key to find the
flow's entry in the meter's flow table.
Counters are incremented for each packet, and are never reset. An
analysis application can compute differences between readings of the
counters, so as to determine rates for these attributes. For
example, if we read flow data at five-minute intervals, we can
calculate five-minute packet and byte rates for the flow's two
directions.
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Times - the FirstTime for a flow is set when its first packet is
observed. LastTime is updated as each packet in the flow is observed.
All the above types have the common feature that they are expressed
as single values. At least some of the new attributes will require
multiple values. If, for example, we are interested in inter-packet
time intervals, we can compute an interval for every packet after
the first. If we are interested in packet sizes, a new value is
obtained as each packet arrives. When it comes to storing this data
we have two options:
- As a distribution, i.e. in an array of 'buckets.' This method is
a compact representation of the data, with the values being stored as
counters between a minimum and maximum, with defined steps in each
bucket. This fits the RTFM goal of compact data storage.
- As a sequence of single values. This saves all the information,
but does not fit well with the RTFM goal of doing as much data
reduction as possible within the meter.
Studies which would be limited by the use of distributions might well
use packet traces instead.
A method for specifying the distribution parameters, and for
encoding the distribution so that it can be easily read, is described
in section 4.2.
3.3 Packet Traces
The simplest way of collecting a trace in the meter would be to have
a new attribute called, say, "PacketTrace." This could be a table,
with a column for each property of interest. For example, one could
trace
- Packet Arrival time (TimeTicks from sysUpTime, or microseconds from
FirstTime for the flow).
- Packet Direction (Forward or Backward)
- Packet Sequence number (for protocols with sequence numbers)
- Packet Flags (for TCP at least).
Note: The following example is for the user who is familiar with the
writing of rule sets for the RTFM Meter.
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To add a row to the table, we only need a rule which PushPkts the
PacketTrace attribute. To use this, one would write a rule set which
selected out a small number of flows of interest, with a 'PushPkt
PacketTrace' rule for each of them. A MaxTraceRows default value of
2000 would be enough to allow a Meter Reader to read one-second ping
traces every 10 minutes or so. More realistically, a MaxTraceRows of
500 would be enough for one-minute pings, read once each hour. Note
that packet traces are already implemented in the RMON MIB [6], in
the Packet Capture Group. They are therefore a low priority for RTFM.
3.4 Aggregate Attributes
RTFM's "old-style" flow attributes count the bytes and packets for
packets which match the rule set for an individual flow. In addition
to these totals, RTFM could calculate Packet Size and Bit Rate
statistics. Bit Rate statistics point to the throughput-related
performance metrics. This data can be stored as distributions, though
it may sometimes be sufficient to simply keep a maximum value.
Packet Size - RTFM's packet flows can be examined to determine the
maximum packet size found in a flow. This will give the Network
Operator an indication of the MTU being used in a flow. It will also
give an indication of the sensitivity to loss of a flow, for losing
large packets causes more data to be retransmitted.
Short-term bit rate - The data could also be recorded as the maximum
and minimum data rate of the flow, found over specific time periods
during the lifetime of a flow; this is a special kind of
'distribution.' Bit rate could be used to define the throughput of a
flow, and if the RTFM flow is defined to be the sum of all traffic in
a network, one can find the throughput of the network.
If we are interested in '10-second' forward data rates, the meter
might compute this for each flow of interest as follows:
- maintain an array of counters to hold the flow's 10-second data
rate distribution.
- every 10 seconds, compute and save 10-second octet count, and save
a copy of the flow's forward octet counter.
To achieve this, the meter will have to keep a list of aggregate
flows and the intervals at which they require processing. Careful
programming will be needed to achieve this, but provided the meter is
not asked to do it for very large numbers of flows, it should not be
too difficult!
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Note that aggregate attributes are a simple extension of the 'old-
style' attributes; their values are never reset. For example, an
array of counters could hold a '10-second bit rate' distribution.
The counters continue to increase, a meter reader will collect their
values at regular intervals, and an analysis application will compute
and display distributions of the 10-second bit rate for each
collection interval.
3.5 Series Attributes
The notion of series attributes is to keep simple statistics for
measures that involve more than one packet. The attribute values
would be stored in the meter as a distribution (see above).
TCP and UDP
Performance aspects of flows are of interest between servers and
clients. We can observe common measurement attributes with TCP/IP
and UDP flows. TCP flows yield additional information due to the
sequence numbers found in TCP. These performance data describe the
performance of a flow as recorded in the locale of the RTFM Meter.
Inter-arrival statistics - TCP and UDP. The Meter knows the time that
it encounters each individual packet. Statistics can be kept to
record the inter-arrival times of the packets, which would give an
indication of the jitter found in the Flow.
Turn-around statistics - TCP and UDP. The Meter knows the time that
it encounters each individual packet. Statistics can be kept to
record the times when packets in opposite directions are found on the
net. This would give an indication of turn around times which have
use for protocols with simple packet flow, e.g. SNMP.
TCP Only - Packet loss - RTFM can calculate packet loss performance
metrics. This is an area for further study. TCP packets have byte
sequence numbers and SYNS, FINS, and ACK's associated with them. RTFM
could track the sequence numbers in the flows, and calculate the
packet loss occurring in a flow, and thus we can develop a metric of
lost packets and useful traffic.
Delay analysis - TCP flows could be examined for the timing between
Transmissions and ACKS and thus we can get some measure of delay (of
IPPM performance metrics). This assumes the forward and reverse
packets are both visible to the meter. In the case of asymmetric
flows, RTFM can be run on multiple paths, and with precise timing
create packet traces, which can be compared at later times.
Subflow analysis - TCP flows, e.g. a Web server's httpd flows
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actually contain many individual sub flows. Given, a well known Web
Server WW, and a client CC, RTFM would normally pick up an
aggregation of all the flows of text, graphics, Java programs, etc.
that are sent between WW and CC. RTFM could detect the TCP handshake
at the beginning of flows, and the Sequence numbers of the flow, and
thus maintain statistics about the subflows within a flow. (A
question for RTFM is whether we will examine fields beyond the
transport header to determine details of the application flow.)
Congestion Analysis - In a TCP/IP flow we have information on the
negotiation of Window sizes which are used by TCP/IP to control
congestion. Well behaved flows honor these requests and in the vast
majority of cases the sender will slow down and thus decrease its
rate of injecting packets into the congested network. We will look
for cases where flows do not honor these congestion controls and are
not slowing down. We will also look for flows which have the
"precedence" fields turned on and thus are aggressively competing for
network resources.
3.6 Actions on Exceptions
The user of RTFM will have the ability to mark flows as having High
Watermarks. The existence of abnormal service conditions, such as
non-ending flow, a flow that exceeds a given limit in traffic (e.g. a
flow that is exhausting the capacity of the line that carries it)
causes an ALERT to be sent to the Meter Reader for forwarding to the
Manager. Operations Support may define service situations in many
different environments. This is an area for further discussion on
Alert and Trap handling.
4. Extensions to the 'Basic' RTFM Meter
The WG has agreed that the basic RTFM Meter will not be altered by
the addition of the new attributes of this document. This section
describes the extensions needed to implement the new attributes.
4.1 Flow table extensions
The architecture of RTFM has defined the structure of flows, and this
draft does not change that structure. The flow table could have
ancillary tables called "Distribution Tables" and "Trace Tables,"
these would contain rows of values and or actions as defined above.
Each entry in these tables would be marked with the number of its
corresponding flow in the RTFM flow table.
Note: The following section is for the user who is familiar with the
writing of rule sets for the RTFM Meter.
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In order to identify the data in a Packet Flow Table, the attribute
name could be pushed into a string at the head of each row. For
example, if a table entry has "To Bit Rate" for a particular flow,
the "ToBitRate" string would be found at the head of the row. (An
alternative method would be to code an identification value for each
extended attribute and push that value into the head of the row.) See
section 5.0 for an inital set of ten extended flow attributes.
4.2. Specifying Distributions in RuleSets
At first sight it would seem neccessary to add extra features to the
RTFM Meter architecture to support distributions. This, however, is
not neccessarily the case.
What is actually needed is a way to specify, in a ruleset, the
distribution parameters. These include the number of counters, the
lower and upper bounds of the distribution, whether it is linear or
logarithmic, and any other details (e.g. the time interval for
short-term rate attributes).
Any attribute which is distribution-valued needs to be allocated a
RuleAttributeNumber value. These will be chosen so as to extend the
list already in the RTFM Meter MIB document [7].
Since distribution attributes are multi-valued it does not make sense
to test them. This means that a PushPkt (or PushPkttoAct) action
must be executed to add a new value to the distribution. The old-
style attributes use the 'mask' field to specify which bits of the
value are required, but again, this is not the case for
distributions. Lastly, the MatchedValue ('value') field of a PushPkt
rule is never used. Overall, therefore, the 'mask' and 'value'
fields in the PushPkt rule are available to specify distribution
parameters.
Both these fields are at least six bytes long, the size of a MAC
address. All we have to do is specify how these bytes should be
used! As a starting point, the following is proposed (bytes are
numbered left-to-right.
Mask bytes:
1 Transform 1 = linear, 2 = logarithmic
2 Scale Factor Power of 10 multiplier for Limits and Counts
3-4 Lower Limit Highest value for first bucket
5-6 Upper Limit Highest value for last bucket
Value bytes:
1-2 Buckets Number of buckets. Does not include
the 'overflow' bucket
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3-4 Parameter-1 Parameter use depends on
5-6 Parameter-2 distribution attribute
For example:
ToPacketSize & .1.0,15,1500 = ,100,0,0: PushPkt, Next
FromBitrate & .2.3,16,2048 = ,7,5,0: PushPkt, Next
In these mask and value fields a dot indicates that the next
number is a one-byte integer, and the commas indicate that the
next number is a two-byte integer.
The first rule specifies that a distribution of packet sizes is
to be built. It uses an array of 100 buckets, storing values
from 1 to 1500 bytes (i.e. linear steps of 15 bytes each). Any
packets with size greater than 1500 will be counted in the 'overflow'
bucket, hence there are 101 counters for the distribution.
The second rule specifies a bit-rate distribution, with the rate
being calculated every 5 seconds (parameter 1). A logarithmic
array of 7 counters (and an overflow bucket) are used for
rates from 16,000 bps to 2,048,000 bps. The scale factor of 3 indicates
that the limits are given in thousands of bits per second.
These distribution parameters will need to be stored in the meter
so that they are available for building the distribution. They
will also need to be read from the meter and saved together with
the other flow data.
4.3 Reading Distributions
Since RTFM flows are bi-directional, each distribution-valued quantity
(e.g. packet size, bit rate, etc.)
will actually need two sets of counters, one for packets travelling in each direction. It is
tempting to regard these as components of a single 'distribution,' but
in many cases only one of the two directions will be of interest; it
seems better to keep them in separate distributions. This is similar
to the old-style counter-valued attributes such as toOctets and fromOctets.
A distribution should be read by a meter reader as a single,
structured object. The components of a distribution object are
- 'mask' and 'value' fields from the rule which created the distribution
- sequence of counters ('buckets' + overflow)
These could be easily collected into a BER-encoded octet string,
and would be read and referred to as a 'distribution.'
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5. Extensions to the Rules Table
The Rules Table of "old-style" attributes will be extended for the
new flow types. A list of actions, and keywords, such as "ToBitRate",
"ToPacketSize", etc. will be developed and
used to inform RTFM to collect a set of extended values for a
particular flow (or set of flows).
Note. An implementation suggestion. Value 65 is used for 'Distributions,' which
has one bit set for each distribution-valued attribute present for the flow, using
bit 0 for attribute 66, bit 1 for attribute 67, etc.
Here are ten possible distribution-valued attributes numbered according to RTFM WG
consensus at the 1997 meeting in Munich:
ToPacketSize(66) size of PDUs in bytes (i.e. number
FromPacketSize(67) of bytes actually transmitted)
ToInterarrivalTime(68) microseconds between successive packets
FromInterarrivalTime(69) travelling in the same direction
ToTurnaroundTime(70) microseconds between successive packets
FromTurnaroundTime(71) travelling in opposite directions
ToBitRate(72) short-term flow rate in bits per second
FromBitRate(73) Parameter 1 = rate interval in seconds
ToPDURate(74) short-term flow rate in PDUs per second
FromPDURate(75) Parameter 1 = rate interval in seconds
6. Security Considerations
The attributes considered in this document represent properties
of traffic flows; they do not present any security issues in
themselves. The attributes may, however, be used in measuring the
behaviour of traffic flows, and the collected traffic flow data
could be of considerable value. Suitable
precautions should be taken to keep such data safe.
7. Acknowledgments
8. Author's Address:
Sig Handelman
IBM Research Division
Hawthorne, NY
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Phone: 1-914-784-7626
E-mail: swhandel@us.ibm.com
Nevil Brownlee
The University of Auckland
New Zealand
Phone: +64 9 373 7599 x8941
E-mail: n.brownlee@auckland.ac.nz
Greg Ruth
GTE Laboratories
Waltham, MA
Phone: 1 781 466 2448
E-mail: grr1@gte.com
Stephen Stibler
IBM Research Division
Hawthorne, NY
Phone: 1-914-784-7191
E-mail: stibler@us.ibm.com
9. References:
[1] Brownlee, N., Mills, C., Ruth, G.: "Traffic Flow Measurement:
Architecture", RFC 2063, 1997
[2] Wroclawski, J.: "The Use of RSVP with IETF Integrated Services"
Internet Draft, October, 1996
[3] Almes, G. et al: "Framework for IP Performance Metrics" Internet
Draft. July 1996
[4] Claffy, K., Braun, H-W, Polyzos, G.: "A Parameterizable
Methodology for Internet Traffic Flow Profiling," IEEE Journal on
Selected Areas in Communications, Vol. 13, No. 8, October 1995.
[5] Mills, C., Ruth, G.: "Internet Accounting Background," RFC 1272,
1992.
[6] Waldbusser, S.: "Remote Network Monitoring Management Information
Base," RFC 1757, 1995, and RFC 2021, 1997.
[7] Brownlee, N: "Traffic Flow Measurement: Meter MIB", RFC 2064,
1997
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