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
                                                 Hawthorne, NY USA

                                                 August 7, 1998
                                                 February 7, 1999

RTFM Working Group - New Attributes for Traffic Flow Measurement


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,
   and its working groups.  Note that other groups may also distribute
   working documents as Internet-Drafts.

   Internet-Drafts are draft documents valid for a maximum of six months
   and may be updated, replaced, or obsoleted by other documents at any
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   To view the entire list of current Internet-Drafts, please check the
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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.  A companion document
   to this draft will be written to define MIB structures for the new

   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

   Implementations of the RTFM 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

   Note on flows and positioning of meters.

   A flow as it traverses the Internet may have some of its
   characteristics altered as it travels through Routers, Switches, and
   other network units. It is important to note the spatial location of
   the Meter when referring to attributes of a flow. An example, a
   server may send a sequence of packets with a definite order, and
   inter packet timing with a leaky bucket algorithm. A meter reading
   downstream of the leaky bucket would record a set with minimal inter
   packet timing due to the leaky bucket. At the client's location, the
   packets may arrive out of sequence, with the timings altered. A meter
   at the client's location would record different attributes for the
   same flow.

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:

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   - 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.

   - 'One-way' (uni-directional) flows are a degenerate case.  Existing
   RTFM meters can handle this by using one of the computed attributes
   e.g. FlowKind) to indicate direction.

   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

   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

   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

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   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 such sequence numbers).

   - In the future, RTFM could coordinate directly with the Flow Label
   from the IPv6 header.

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. An initial
   implementation of IIS Monitoring has been developd at CEFRIEL in
   Italy [8].

   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,

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   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 'trace' - attributes of individual packets in a flow or a segment
   of a flow (e.g. last packet size, last packet arrival time).

   o 'aggregates' - statistics derived from the flow taken as a whole
   (e.g. mean rate, max packet size, packet size distribution).

   o 'group'- attributes that depend on groups of packet values within
   the flow (e.g. inter-arrival times, short-term traffic rates).

   Note that attributes within each of these classes may have various
   types of values - numbers, distributions, time series, and so on.

   3.1. Meter Readers and Meters

   A note on the relation between Meter Readers and Meters.

   Several of the measurements enumerated below can be implemented by a
   Meter Reader that is tied to the meter with very short 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 directly to the Meter Reader for further

   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.  Their
   types are

   - Addresses, represented as byte strings (1 to 20 bytes long)

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   - 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

   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

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   - 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 implementation proposal is for the user who is
   familiar with the writing of rule sets for the RTFM Meter.

   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.

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   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 is needed to achieve this, but provided the meter is not
   asked to do it for very large numbers of flows, it has been
   successfully implemented.

   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 Group Attributes

   The notion of group attributes is to keep simple statistics for
   measures that involve more than one packet.  This section describes
   some group attributes which it is feasible to implement in a traffic
   meter, and which seem interesting and useful.

   Inter-arrival times. 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.  Sine the Meter knows the time that it
   encounters each individual packet, it can produce statistics of the
   time intervals between packets in opposite directions are observed on
   the network.  For protocols such as SNMP (where every packet elicits
   an answering packet) this gives a good indication of turn-around

   Subflow analysis.  Since the choice of flow endpoints is controlled
   by the meter's rule set, it is easy to define an aggregate flow, e.g
   "all the TCP streams between hosts A and B."  Preliminary
   implementation work suggests that - at least for this case - it
   should be possible for the meter to maintain a table of information
   about all the active streams.  This could be used to produce at least

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   the following attributes:
    - Number of streams, e.g. streams active for n-second intervals.
         Determined for TCP and UDP using source-dest port number pairs.
    - Number of TCP bytes, determined by taking difference of TCP
         sequence numbers for each direction of the aggreagate flow.

   IIS attributes.  Work at CEFRIEL [8] has produced a traffic meter
   with a rule set modified 'on the fly' so as to maintain a list of
   RSVP-reserved flows.  For such flows the following attributes have
   been implemented (these quantities are defined in [9]):

      - QoSService:          Service class for the flow
                               (guaranteed, controlled load)
      - QoSStyle:            Reservation setup style
                               (wildcard filter, fixed filter,
                               shared explicit)
      - QoSRate:             [byte/s] rate for flows with
                               guaranteed service
      - QoSSlackTerm:        [microseconds] Slack Term QoS parameter
                               for flows with guaranteed service
      - QoSTokenBucketRate:  [byte/s] Token Bucket Rate QoS parameter
                               for flows with guaranteed or
                               controlled load service

      The following are also being considered:

      - QoSTokenBucketSize:  [byte] Size of Token Bucket

      - QoSPeakDataRate:     [byte/s] Maximum rate for incoming data

      - QoSMinPolicedUnit:   [byte] IP datagrams less than this are
                               counted as being this size
      - QoSMaxDatagramSize:  [byte] Size of biggest datagram which
                               conforms to the traffic specification

3.6 Actions on Exceptions

   Some users of RTFM have requested 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) would cause an ALERT to be sent to the Meter Reader for
   forwarding to the Manager. Operations Support could 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

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   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.

   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

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   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    Buckets          Number of buckets.  Does not include
                                  the 'overflow' bucket
        2    Parameter-1      } Parameter use depends
      3-4    Parameter-2      } on distribution-valued
      5-6    Parameter-3      } attribute

   For example:

      FromPacketSize     & 1.0.25!1500 = 60.0!0:   PushPkttoAct, Next;

      ToInterArrivalTime &  2.3.1!1800 = 60.0.0!0: PushPkttoAct, Next;

      FromBitRate        & 2.3.1!10000 = 60.5.0!0: PushPkttoAct, Next;

   In these mask and value fields a dot indicates that the preceding
   number is a one-byte integer, the exclamation marks indicate that
   the preceding number is a two-byte integer, and the last number is
   two bytes wide since this was the width of the preceding field.
   (Note that this convention follows that for IP addresses - 130.216

   The first rule specifies that a distribution of packet sizes is
   to be built.  It uses an array of 60 buckets, storing values from
   1 to 1500 bytes (i.e. linear steps of 25 bytes each bucket).  Any
   packets with size greater than 1500 will be counted in the

   The second rule specifies an arrival-time distribution, using a
   logarithmic scale for an array of 60 counters (and an overflow
   bucket) for rates from 1 ms to 1.8 s.  The scale factor of 3
   indicates that the limits are given in milliseconds.

   The third rule specifies a bit-rate distribution, with the rate
   being calculated every 5 seconds (parameter 1).  A logarithmic
   array of 60 counters (and an overflow bucket) are used for

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   rates from 1 kbps to 10 Mbps.  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 can be easily collected into a BER-encoded octet string,
   and would be read and referred to as a 'distribution.'

5. Extensions to the Rules Table

   Extensions to the Rules Table, Attribute Numbers

   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 an RTFM
   meter 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)

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      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

      (76 .. 97)                 other distributions

      It seems reasonable to allocate a further group of numbers
      for the IIS attributes described above -


   The following attributes have also been implemented in NetFlowMet, a
   version of the NeTraMet meter -

      MeterID(112)        Integer identifying the router producing
                             NetFlow data (needed when NetFlowMet takes
                             data from several routers)
      SourceASN(113)      Autonomous System Number for flow's source
      SourcePrefix(114)   CIDR width used by router for determining
                             flow's source network
      DestASN(115)        Autonomous System Number for flow's destination
      DestPrefix(116)     CIDR width used by router for determining
                             flow's destination network

   Some of the above, e.g. SourceASN and DestASN, might sensibly be
   allocated attribute numbers below 64, making them part of the 'base'
   RTFM meter attributes.

6. Security Considerations

   The attributes considered in this document represent properties
   of traffic flows; they do not present any security issues in

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   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
   Phone: 1-914-784-7626

   Nevil Brownlee
   The University of Auckland
   New Zealand
   Phone: +64 9 373 7599 x8941

   Greg Ruth
   GTE Laboratories
   Waltham, MA
   Phone: 1 781 466 2448

   Stephen Stibler
   IBM Research Division
   Hawthorne, NY
   Phone: 1-914-784-7191

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

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   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,

   [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,

   [8] Maiocchi, S: "NeTraMet & NeMaC for IIS Accounting: User's Guide",
   CEFRIEL, Milan, 5 May 1998, (See also,

   [9] Shenker, S., Partridge, C., Guerin, R.: "Specification of
   Guaranteed Quality of Service," RFC 2212, 1997.

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