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

                                                   S. Stibler
                                                   IBM
                                                   Hawthorne, NY USA

                                                   March 13, 1998
                                                   expires
                                                   January 20,
                                                   September 13, 1998

RTFM Working Group - New Attributes for Traffic Flow Measurement

<draft-ietf-rtfm-new-traffic-flow-02.txt>

<draft-ietf-rtfm-new-traffic-flow-03.txt>

1. Status of this Memo

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   This memo provides information for the Internet community.  This memo
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2. Introduction

   The Real-time Traffic 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]
   and [5]. [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 rates. volumes. Performance attributes
   typically deal with throughput, packet loss, and delays.
   We The WG will
   explore the methods by which RTFM can extract values from packets and
   flows so as to measure these attributes. We The WG will also look at
   capturing information on jitter and congestion control.

   The RTFM Working Group has defined A companion
   document to this draft will be written to define the concept 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 standardized
   meter simple set of abstractions,
   which records flows from can be easily implemented and at the same time enhance the
   value of RTFM Meters.  This document also defines a traffic stream according method for
   organizing the flow abstractions to Rule
   Sets which are active in augment the meter[1]. existing RTFM flow
   table.

   Implementations of this 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 Program whose job role is to fetch 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 end-points endpoints (as defined by their source and destination attribute
   values),
   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:

   - We are The WG is 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. 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.

   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 which is that does not
   classified by
   match the Rule Set into 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 number Label
   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.

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 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 Meter could act as a passive device that, device, 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 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 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.

   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 Meter calculate some flow
   statistics locally. This allows a looser coupling between the meter Meter
   and Meter Reader. RTFM will create 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.

3.1. Attrubute

3.2. Attribute Types

   The previous section

   Section 3.0 described three different classes of attribute; attributes; this
   section considers what the types "data types" of these attributes could be. 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,' and will not
   be considered further here. objects' i.e. lists of
   attribute values for a string of packets.

   Aggregate attributes are like the 'old-style' ones.  Their 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 set 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.

   Times - the FirstTime for a flow is set when its first packet is
   observed. LastTime is updated for every as each packet of in the flow. 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
   produced
   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.' On  This method is
   a compact representation of the other hand
   meter storage requirements are well-defined, data, with the values being stored as is
   counters between a minimum and maximum, with defined steps in each
   bucket. This fits the amount RTFM goal of compact data
   to be read from the meter. storage.

   - As a sequence of integers. 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.

   For most of RTFM's attributes, a 'distribution' (as described above)
   appears to be the most effective attribute type.

   A method of  for specifying the distribution parameters, and for
   encoding the distribution so that it can be easily read, are is described
   in section 4.2.

3.2.

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, 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.

   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 one-second ping
   traces every 10 minutes or so.  More realistically, a MaxTraceRows of
   500 would be enough for one- minute 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 Group. They are therefore a low priority for RTFM.

3.3

3.4  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 Size and Bit rate Rate
   statistics. Bit rate 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 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. 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 the 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!
   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.

3.4

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

   Inter-arrival 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 inter-arrival times of when packets in opposite directions are found on the packets, which
   net. This  would give an indication of the jitter found in the Flow. 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
   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,  detect the TCP handshake
   at the beginning of flows, and the Sequence numbers of the flow, and
   thus maintain statistics about the subflows on within a network. 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 control 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.

3.5

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.

   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 Rates Rate" for a particular flow,
   the
   "BitRate" "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 'overflows' 'overflow' bucket
   3-4    Parameter-1      Parameter use depends on
   5-6    Parameter-2      distribution attribute

   For example:

   ToPacketSize & 1.0,1,1500 .1.0,15,1500 = 100,0,0: ,100,0,0:  PushPkt, Next

    FromBitrate & 2.3,16,2048 .2.3,16,2048 = 7,5,0: ,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 16,000 bps to 2048 kbps. 2,048,000 bps.  The scale factor of 10 3 indicates
   that the limits are given in kilobits 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 sensible; 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' field 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.'

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, keywords, such as "BitRate"-
   for Bit Rate, "MaxPackSize", for Max Packet size "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).

   To begin with, here

   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:

   ToPacketSize(61) attributes numbered according to RTFM WG
   consensus at the 1997 meeting in Munich:

   ToPacketSize(66)           size of PDUs in bytes (i.e. number
   FromPacketSize(62)
   FromPacketSize(67)           of bytes actually transmitted)

   ToInterarrivalTime(63)

   ToInterarrivalTime(68)     microseconds between successive packets
   FromInterarrivalTime(64)
   FromInterarrivalTime(69)     travelling in the same direction

   ToTurnaroundTime(65)

   ToTurnaroundTime(70)       microseconds between successive packets
   FromTurnaroundTime(66)
   FromTurnaroundTime(71)       travelling in opposite directions

   ToBitRate(67)

   ToBitRate(72)              short-term flow rate in bits per second
   FromBitRate(68)
   FromBitRate(73)              Parameter 1 = rate interval in seconds

   ToPDURate(69)

   ToPDURate(74)              short-term flow rate in PDUs per second
   FromPDURate(70)
   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.
   Anyone making such measurments should have a clearly-defined
   purpose in doing so.  They Suitable
   precautions should also take great care be taken to ensure
   that the keep such data is properly stored, and is used solely for its
   intended purpose. safe.

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 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: 1 617 781 466 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"
   [3] Almes, G. et al: "Framework for IP Performance Metrics" Internet
   [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