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
July 20, 1997
expires
January 20, 1998
RTFM Working Group - New Attributes for Traffic Flow Measurement
<draft-ietf-rtfm-new-traffic-flow-02.txt>
1. Status of this Memo
This document is an Internet Draft. Internet Drafts are working
documents of the Internet Engineering Task Force (IETF), its areas,
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ftp.isi.edu (US West Coast).
This memo provides information for the Internet community. This memo
does not specify an Internet standard of any kind. Distribution of
this memo is unlimited.
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2. Introduction
The Real-time Traffic Flow Measurement (RTFM) Working Group 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]
and [5]. The new attributes described in this document will be
useful for monitoring network performance and expand the scope of
RTFM beyond simple measurement of traffic rates. Performance
attributes typically deal with throughput, packet loss, and delays.
We will explore the methods by which RTFM can extract values from
flows so as to measure these attributes. We will also look at
capturing information on jitter and congestion control.
The RTFM Working Group has defined the concept of a standardized
meter which records flows from a traffic stream according to Rule
Sets which are active in the meter[1].
Implementations of this 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 Meter
Reader Program whose job is to fetch 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 end-points (as defined by their source and destination attribute
values), and as BI-DIRECTIONAL (i.e. the meter effectively monitors
two sub-flows, one in each direction).
Reasons why RTFM flows are bi-directional:
- We are interested in understanding the behavior of sessions between
end-points.
- We want to perform as much data reduction as possible, so as to
reduce the amount of data to be retrieved from a remote meter.
- 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.
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
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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 which is not
classified by the Rule Set into 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 byte counters, one for each flow
direction (Forward and Backward). These are updated as packets 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 number
from the IPv6 header.
At the June, 1996 meeting of the RTFM WG in Montreal, Canada, a
proposal was made to extend the work of the group to produce an
Internet Draft "New Attributes for Traffic Flow Measurement". That
proposal has brought forth this document. 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
preserve the existing RTFM flow table.
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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. We 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 that, gathering traffic
and performance statistics at appropriate places in TCP/IP 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 the 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 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).
The following sections suggest implementations for each of these
classes of extensions.
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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
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 create 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.
3.1. Attrubute Types
The previous section described three different classes of attribute;
this section considers what the types of these attributes could be.
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,' and will not
be considered further here.
Aggregate attributes are like the 'old-style' ones. Their 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 set 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.
Times - the FirstTime for a flow is set when its first packet is
observed. LastTime is updated for every packet of the flow.
All the above types have the common feature that they are expressed
as single values. At least some of the new attributes will require
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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
produced 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.' On the other hand
meter storage requirements are well-defined, as is the amount of data
to be read from the meter.
- As a sequence of integers. 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.
For most of RTFM's attributes, a 'distribution' (as described above)
appears to be the most effective attribute type. A method of
specifying the distribution parameters, and for encoding the
distribution so that it can be easily read, are described in section
4.2.
3.2. 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
- Arrival time (TimeTicks from SysUptime, or microseconds from
FirstTime for the flow).
- Direction (Forward or Backward)
- Sequence number (for protocols with sequence numbers)
- Flags (for TCP at least).
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 1-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
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the Packet Capture Group; they are therefore a low priority for RTFM.
3.3 Aggregate Attributes
Performance aspects of flows are of interest in the case of a flow
between a server and client. TCP/IP and UDP flows contain equivalent
performance, with additional data from TCP flows. The performance
data found by this method define the flow capacity used by the
individual flow, as experienced in the locale of the RTFM meter.
For both TCP/IP and UDP, 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.
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 repeated.
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 the 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!
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.
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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.
3.4 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
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.
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
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. By analyzing the Sequence numbers,
RTFM could estimate when each subflow occurs, and thus maintain
statistics about the subflows on a network.
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 control and are
not slowing down. We will also look for flows which have the
"precedence" fields turned on and thus are aggressively competing for
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network resources.
3.5 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
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.
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 Bit Rates for a particular flow, the
"BitRate" string would be found at the head of the row.
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
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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 'overflows' bucket
3-4 Parameter-1 Parameter use depends on
5-6 Parameter-2 distribution attribute
For example:
ToPacketSize & 1.0,1,1500 = 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 kbps to 2048 kbps. The scale factor of 10 indicates
that the limits are given in kilobits per second.
These distribution parameters will need to be stored in the meter
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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 sensible; 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' field from rule which created the distribution
- sequence of counters ('buckets' + overflow)
These could be easily collected into a BER-encoded octet string,
and be read and referred to as a 'distribution.'
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 "BitRate"-
for Bit Rate, "MaxPackSize", for Max Packet size will be developed and
used to inform RTFM to collect a set of extended values for a
particular flow (or set of flows).
To begin with, here are ten possible distribution-valued attributes:
ToPacketSize(61) size of PDUs in bytes (i.e. number
FromPacketSize(62) of bytes actually transmitted)
ToInterarrivalTime(63) microseconds between successive packets
FromInterarrivalTime(64) travelling in the same direction
ToTurnaroundTime(65) microseconds between successive packets
FromTurnaroundTime(66) travelling in opposite directions
ToBitRate(67) short-term flow rate in bits per second
FromBitRate(68) Parameter 1 = rate interval in seconds
ToPDURate(69) short-term flow rate in PDUs per second
FromPDURate(70) Parameter 1 = rate interval in seconds
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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.
Anyone making such measurments should have a clearly-defined
purpose in doing so. They should also take great care to ensure
that the data is properly stored, and is used solely for its
intended purpose.
7. Acknowledgments
We thank Stephen Stibler of IBM for his input to, and comments on this draft.
8. Author's Address:
Sig Handelman
IBM Research Division
Hawthorne, NY
Phone: 1-914-784-7626
E-mail: handel@watson.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: 1 617 466 2448
E-mail: grr1@gte.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
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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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