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RFC2063 - Traffic Flow Measurement: Architecture

王朝other·作者佚名  2008-05-31
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Network Working Group N. Brownlee

Request for Comments: 2063 The University of AUCkland

Category: EXPerimental C. Mills

BBN Systems and Technologies

G. Ruth

GTE Laboratories, Inc.

January 1997

Traffic Flow Measurement: Architecture

Status of this Memo

This memo defines an Experimental Protocol for the Internet

community. This memo does not specify an Internet standard of any

kind. Discussion and suggestions for improvement are requested.

Distribution of this memo is unlimited.

Abstract

This document describes an architecture for the measurement and

reporting of network traffic flows, discusses how this relates to an

overall network traffic flow architecture, and describes how it can

be used within the Internet. It is intended to provide a starting

point for the Realtime Traffic Flow Measurement Working Group.

Table of Contents

1 Statement of Purpose and Scope 2

2 Traffic Flow Measurement Architecture 4

2.1 Meters and Traffic Flows . . . . . . . . . . . . . . . . . . 4

2.2 Interaction Between METER and METER READER . . . . . . . . . 6

2.3 Interaction Between MANAGER and METER . . . . . . . . . . . 6

2.4 Interaction Between MANAGER and METER READER . . . . . . . . 7

2.5 Multiple METERs or METER READERs . . . . . . . . . . . . . . 7

2.6 Interaction Between MANAGERs (MANAGER - MANAGER) . . . . . . 8

2.7 METER READERs and APPLICATIONs . . . . . . . . . . . . . . . 8

3 Traffic Flows and Reporting Granularity 9

3.1 Flows and their Attributes . . . . . . . . . . . . . . . . . 9

3.2 Granularity of Flow Measurements . . . . . . . . . . . . . . 11

3.3 Rolling Counters, Timestamps, Report-in-One-Bucket-Only . . 13

4 Meters 15

4.1 Meter Structure . . . . . . . . . . . . . . . . . . . . . . 15

4.2 Flow Table . . . . . . . . . . . . . . . . . . . . . . . . . 17

4.3 Packet Handling, Packet Matching . . . . . . . . . . . . . . 17

4.4 Rules and Rule Sets . . . . . . . . . . . . . . . . . . . . 21

4.5 Maintaining the Flow Table . . . . . . . . . . . . . . . . . 24

4.6 Handling Increasing Traffic Levels . . . . . . . . . . . . . 25

5 Meter Readers 26

5.1 Identifying Flows in Flow Records . . . . . . . . . . . . . 26

5.2 Usage Records, Flow Data Files . . . . . . . . . . . . . . . 27

5.3 Meter to Meter Reader: Usage Record Transmission. . . . . . 27

6 Managers 28

6.1 Between Manager and Meter: Control Functions . . . . . . . 28

6.2 Between Manager and Meter Reader: Control Functions . . . 29

6.3 Exception Conditions . . . . . . . . . . . . . . . . . . . . 31

6.4 Standard Rule Sets . . . . . . . . . . . . . . . . . . . . 32

7 APPENDICES 33

7.1 Appendix A: Network Characterisation . . . . . . . . . . . . 33

7.2 Appendix B: Recommended Traffic Flow Measurement Capabilities 34

7.3 Appendix C: List of Defined Flow Attributes . . . . . . . . 35

7.4 Appendix D: List of Meter Control Variables . . . . . . . . 36

8 Acknowledgments 36

9 References 37

10 Security Considerations 37

11 Authors' Addresses 37

1 Statement of Purpose and Scope

This document describes an architecture for traffic flow measurement

and reporting for data networks which has the following

characteristics:

- The traffic flow model can be consistently applied to any

protocol/application at any network layer (e.g. network,

transport, application layers).

- Traffic flow attributes are defined in such a way that they are

valid for multiple networking protocol stacks, and that traffic

flow measurement implementations are useful in MULTI-PROTOCOL

environments.

- Users may specify their traffic flow measurement requirements

in a simple manner, allowing them to collect the flow data they

need while ignoring other traffic.

- The data reduction effort to produce requested traffic flow

information is placed as near as possible to the network

measurement point. This reduces the volume of data to be

oBTained (and transmitted across the network for storage),

and minimises the amount of processing required in traffic

flow analysis applications.

The architecture specifies common metrics for measuring traffic

flows. By using the same metrics, traffic flow data can be exchanged

and compared across multiple platforms. Such data is useful for:

- Understanding the behaviour of existing networks,

- Planning for network development and expansion,

- Quantification of network performance,

- Verifying the quality of network service, and

- Attribution of network usage to users.

The traffic flow measurement architecture is deliberately structured

so that specific protocol implementations may extend coverage to

multi-protocol environments and to other protocol layers, such as

usage measurement for application-level services. Use of the same

model for both network- and application-level measurement may

simplify the development of generic analysis applications which

process and/or correlate any or all levels of traffic and usage

information. Within this docuemt the term 'usage data' is used as a

generic term for the data obtained using the traffic flow measurement

architecture.

This document is not a protocol specification. It specifies and

structures the information that a traffic flow measurement system

needs to collect, describes requirements that such a system must

meet, and outlines tradeoffs which may be made by an implementor.

For performance reasons, it may be desirable to use traffic

information gathered through traffic flow measurement in lieu of

network statistics obtained in other ways. Although the

quantification of network performance is not the primary purpose of

this architecture, the measured traffic flow data may be used as an

indication of network performance.

A cost recovery structure decides "who pays for what." The major

issue here is how to construct a tariff (who gets billed, how much,

for which things, based on what information, etc). Tariff issues

include fairness, predictability (how well can subscribers forecast

their network charges), practicality (of gathering the data and

administering the tariff), incentives (e.g. encouraging off-peak

use), and cost recovery goals (100% recovery, subsidisation, profit

making). Issues such as these are not covered here.

Background information explaining why this approach was selected is

provided by 'Traffic Flow Measurement: Background' RFC[1].

2 Traffic Flow Measurement Architecture

A traffic flow measurement system is used by network Operations

personnel for managing and developing a network. It provides a tool

for measuring and understanding the network's traffic flows. This

information is useful for many purposes, as mentioned in section 1

(above).

The following sections outline a model for traffic flow measurement,

which draws from working drafts of the OSI accounting model [2].

Future extensions are anticipated as the model is refined to address

additional protocol layers.

2.1 Meters and Traffic Flows

At the heart of the traffic measurement model are network entities

called traffic METERS. Meters count certain attributes (such as

numbers of packets and bytes) and classify them as belonging to

ACCOUNTABLE ENTITIES using other attributes (such as source and

destination addresses). An accountable entity is someone who (or

something which) is responsible for some activitiy on the network.

It may be a user, a host system, a network, a group of networks, etc,

depending on the granularity specified by the meter's configuration.

We assume that routers or traffic monitors throughout a network are

instrumented with meters to measure traffic. Issues surrounding the

choice of meter placement are discussed in the 'Traffic Flow

Measurement: Background' RFC[1]. An important ASPect of meters is

that they provide a way of succinctly aggregating entity usage

information.

For the purpose of traffic flow measurement we define the concept of

a TRAFFIC FLOW, which is an artificial logical equivalent to a call

or connection. A flow is a portion of traffic, delimited by a start

and stop time, that was generated by a particular accountable entity.

Attribute values (source/destination addresses, packet counts, byte

counts, etc.) associated with a flow are aggregate quantities

reflecting events which take place in the DURATION between the start

and stop times. The start time of a flow is fixed for a given flow;

the end time may increase with the age of the flow.

For connectionless network protocols such as IP there is by

definition no way to tell whether a packet with a particular

source/destination combination is part of a stream of packets or not

- each packet is completely independent. A traffic meter has, as

part of its configuration, a set of 'rules' which specify the flows

of interest, in terms of the values of their attributes. It derives

attribute values from each observed packet, and uses these to decide

which flow they belong to. Classifying packets into 'flows' in this

way provides an economical and practical way to measure network

traffic and ascribe it to accountable entities.

Usage information which is not deriveable from traffic flows may also

be of interest. For example, an application may wish to record

Accesses to various different information resources or a host may

wish to record the username (subscriber id) for a particular network

session. Provision is made in the traffic flow architecture to do

this. In the future the measurement model will be extended to gather

such information from applications and hosts so as to provide values

for higher-layer flow attributes.

As well as FLOWS and METERS, the traffic flow measurement model

includes MANAGERS, METER READERS and ANALYSIS APPLICAIONS, which are

explained in following sections. The relationships between them are

shown by the diagram below. Numbers on the diagram refer to sections

in this document.

MANAGER

/ 2.3 / \ 2.4

/ / \ ANALYSIS

METER <-----> METER READER <-----> APPLICATION

2.2 2.7

- MANAGER: A traffic measurement manager is an application which

configures 'meter' entities and controls 'meter reader' entities.

It uses the data requirements of analysis applications to determine

the appropriate configurations for each meter, and the proper

operation of each meter reader. It may well be convenient to

combine the functions of meter reader and manager within a single

network entity.

- METER: Meters are placed at measurement points determined by

network Operations personnel. Each meter selectively records

network activity as directed by its configuration settings. It can

also aggregate, transform and further process the recorded activity

before the data is stored. The processed and stored results are

called the 'usage data.'

- METER READER: A meter reader reliably transports usage data from

meters so that it is available to analysis applications.

- ANALYSIS APPLICATION: An analysis application processes the usage

data so as to provide information and reports which are useful for

network engineering and management purposes. Examples include:

- TRAFFIC FLOW MATRICES, showing the total flow rates for

many of the possible paths within an internet.

- FLOW RATE FREQUENCY DISTRIBUTIONS, indicating how flow

rates vary with time.

- USAGE DATA showing the total traffic volumes sent and

received by particular hosts.

The operation of the traffic measurement system as a whole is best

understood by considering the interactions between its components.

These are described in the following sections.

2.2 Interaction Between METER and METER READER

The information which travels along this path is the usage data

itself. A meter holds usage data in an array of flow data records

known as the FLOW TABLE. A meter reader may collect the data in any

suitable manner. For example it might upload a copy of the whole

flow table using a file transfer protocol, or read the records in the

current flow set one at a time using a suitable data transfer

protocol. Note that the meter reader need not read complete flow

data records, a subset of their attribute values may well be

sufficient.

A meter reader may collect usage data from one or more meters. Data

may be collected from the meters at any time. There is no

requirement for collections to be synchronized in any way.

2.3 Interaction Between MANAGER and METER

A manager is responsible for configuring and controlling one or more

meters. At the time of writing a meter can only be controlled by a

single manager; in the future this restriction may be relaxed. Each

meter's configuration includes information such as:

- Flow specifications, e.g. which traffic flows are to be measured,

how they are to be aggregated, and any data the meter is required

to compute for each flow being measured.

- Meter control parameters, e.g. the maximum size of its flow table,

the 'inactivity' time for flows (if no packets belonging to a flow

are seen for this time the flow is considered to have ended, i.e.

to have become idle).

- Sampling rate. Normally every packet will be observed. It may

sometimes be necessary to use sampling techniques to observe only

some of the packets. (Sampling algorithms are not prescribed by

the architecture; it should be noted that before using sampling one

should verify the statistical validity of the algorithm used).

Current experience with the measurement architecture shows that a

carefully-designed and implemented meter compresses the data such

that in normal LANs and WANs of today sampling is really not

needed.

2.4 Interaction Between MANAGER and METER READER

A manager is responsible for configuring and controlling one or more

meter readers. A meter reader may only be controlled by a single

manager. A meter reader needs to know at least the following for

every meter is is collecting usage data from:

- The meter's unique identity, i.e. its network name or address.

- How often usage data is to be collected from the meter.

- Which flow records are to be collected (e.g. all active flows, the

whole flow table, flows seen since a given time, etc.).

- Which attribute values are to be collected for the required flow

records (e.g. all attributes, or a small subset of them)

Since redundant reporting may be used in order to increase the

reliability of usage data, exchanges among multiple entities must be

considered as well. These are discussed below.

2.5 Multiple METERs or METER READERs

-- METER READER A --

/ / =====METER 1 METER 2=====METER 3 METER 4=====

\ /

\ /

-- METER READER B --

Several uniquely identified meters may report to one or more meter

readers. The diagram above gives an example of how multiple meters

and meter readers could be used.

In the diagram above meter 1 is read by meter reader A, and meter 4

is read by meter reader B. Meters 1 and 4 have no redundancy; if

either fails, usage data for their network segments will be lost.

Meters 2 and 3, however, measure traffic on the same network segment.

One of them may fail leaving the other collecting the segment's usage

data. Meters 2 and 3 are read by meter reader A and by meter reader

B. If one meter reader fails, the other will continue collecting

usage data.

The architecture does not require multiple meter readers to be

synchronized. In the situation above meter readers A and B could

both collect usage data at the same intervals, but not neccesarily at

the same times. Note that because collections are asynchronous it is

unlikely that usage records from two different meter readers will

agree exactly.

If precisely synchronized collections are required this can be

achieved by having one manager request each meter to begin collecting

a new set of flows, then allowing all meter readers to collect the

usage data from the old sets of flows.

If there is only one meter reader and it fails, the meters continue

to run. When the meter reader is restarted it can collect all of the

accumulated flow data. Should this happen, time resolution will be

lost (because of the missed collections) but overall traffic flow

information will not. The only exception to this would occur if the

traffic volume was sufficient to 'roll over' counters for some flows

during the failure; this is addressed in the section on 'Rolling

Counters.'

2.6 Interaction Between MANAGERs (MANAGER - MANAGER)

Synchronization between multiple management systems is the province

of network management protocols. This traffic flow measurement

architecture specifies only the network management controls necessary

to perform the traffic flow measurement function and does not address

the more global issues of simultaneous or interleaved (possibly

conflicting) commands from multiple network management stations or

the process of transferring control from one network management

station to another.

2.7 METER READERs and APPLICATIONs

Once a collection of usage data has been assembled by a meter reader

it can be processed by an analysis application. Details of analysis

applications - such as the reports they produce and the data they

require - are outside the scope of this architecture.

It should be noted, however, that analysis applications will often

require considerable amounts of input data. An important part of

running a traffic flow measurement system is the storage and regular

reduction of flow data so as to produce daily, weekly or monthly

summary files for further analysis. Again, details of such data

handling are outside the scope of this architecture.

3 Traffic Flows and Reporting Granularity

A flow was defined in section 2.1 above in abstract terms as follows:

"A TRAFFIC FLOW is an artifical logical equivalent to a call or

connection, belonging to an ACCOUNTABLE ENTITY."

In practical terms, a flow is a stream of packets passing across a

network between two end points (or being sent from a single end

point), which have been summarized by a traffic meter for analysis

purposes.

3.1 Flows and their Attributes

Every traffic meter maintains a table of 'flow records' for flows

seen by the meter. A flow record holds the values of the ATTRIBUTES

of interest for its flow. These attributes might include:

- ADDRESSES for the flow's source and destination. These comprise

the protocol type, the source and destination addresses at various

network layers (extracted from the packet), and the number of the

interface on which the packet was observed.

- First and last TIMES when packets were seen for this flow, i.e.

the 'creation' and 'last activity' times for the flow.

- COUNTS for 'forward' (source to destination) and 'backward'

(destination to source) components (e.g. packets and bytes) of the

flow's traffic. The specifying of 'source' and 'destination' for

flows is discussed in the section on packet matching below.

- OTHER attributes, e.g. information computed by the meter.

A flow's ACCOUNTABLE ENTITY is specified by the values of its ADDRESS

attributes. For example, if a flow's address attributes specified

only that "source address = IP address 10.1.0.1," then all IP packets

from and to that address would be counted in that flow. If a flow's

address list were specified as "source address = IP address 10.1.0.1,

destination address = IP address 26.1.0.1" then only IP packets

between 10.1.0.1 and 26.1.0.1 would be counted in that flow.

The addresses specifying a flow's address attributes may include one

or more of the following types:

- The INTERFACE NUMBER for the flow, i.e. the interface on which the

meter measured the traffic. Together with a unique address for the

meter this uniquely identifies a particular physical-level port.

- The ADJACENT ADDRESS, i.e. the [n-1] layer address of the

immediate source or destination on the path of the packet. For

example, if flow measurement is being performed at the IP layer on

an Ethernet LAN [3], an adjacent address is a six-octet Media

Access Control (MAC) address. For a host connected to the same LAN

segment as the meter the adjacent address will be the MAC address

of that host. For hosts on other LAN segments it will be the MAC

address of the adjacent (upstream or downstream) router carrying

the traffic flow.

- The PEER ADDRESS, which identifies the source or destination of the

PEER-LEVEL packet. The form of a peer address will depend on the

network-layer protocol in use, and the network layer [n] at which

traffic measurement is being performed.

- The TRANSPORT ADDRESS, which identifies the source or destination

port for the packet, i.e. its [n+1] layer address. For example,

if flow measurement is being performed at the IP layer a transport

address is a two-octet UDP or TCP port number.

The four definitions above specify addresses for each of the four

lowest layers of the OSI reference model, i.e. Physical layer, Link

layer, Network layer and Transport layer. A FLOW RECORD stores both

the VALUE for each of its addresses (as described above) and a MASK

specifying which bits of the address value are being used and which

are ignored. Note that if address bits are being ignored the meter

will set them to zero, however their actual values are undefined.

One of the key features of the traffic measurement architecture is

that attributes have essentially the same meaning for different

protocols, so that analysis applications can use the same reporting

formats for all protocols. This is straightforward for peer

addresses; although the form of addresses differs for the various

protocols, the meaning of a 'peer address' remains the same. It

becomes harder to maintain this correspondence at higher layers - for

example, at the Network layer IP, Novell IPX and AppleTalk all use

port numbers as a 'transport address,' but CLNP and DECnet have no

notion of ports. Further work is needed here, particularly in

selecting attributes which will be suitable for the higher layers of

the OSI reference model.

Reporting by adjacent intermediate sources and destinations or simply

by meter interface (most useful when the meter is embedded in a

router) supports hierarchical Internet reporting schemes as described

in the 'Traffic Flow Measurement: Background' RFC[1]. That is, it

allows backbone and regional networks to measure usage to just the

next lower level of granularity (i.e. to the regional and

stub/enterprise levels, respectively), with the final breakdown

according to end user (e.g. to source IP address) performed by the

stub/enterprise networks.

In cases where network addresses are dynamically allocated (e.g.

mobile subscribers), further subscriber identification will be

necessary if flows are to ascribed to individual users. Provision is

made to further specify the accountable entity through the use of an

optional SUBSCRIBER ID as part of the flow id. A subscriber ID may

be associated with a particular flow either through the current rule

set or by proprietary means within a meter, for example via protocol

exchanges with one or more (multi-user) hosts. At this time a

subscriber ID is an arbitrary text string; later versions of the

architecture may specify its contents on more detail.

3.2 Granularity of Flow Measurements

GRANULARITY is the 'control knob' by which an application and/or the

meter can trade off the overhead associated with performing usage

reporting against the level of detail supplied. A coarser

granularity means a greater level of aggregation; finer granularity

means a greater level of detail. Thus, the number of flows measured

(and stored) at a meter can be regulated by changing the granularity

of the accountable entity, the attributes, or the time intervals.

Flows are like an adjustable pipe - many fine-granularity streams can

carry the data with each stream measured individually, or data can be

bundled in one coarse-granularity pipe.

Flow granularity is controlled by adjusting the level of detail at

which the following are reported:

- The accountable entity (address attributes, discussed above).

- The categorisation of packets (other attributes, discussed below).

- The lifetime/duration of flows (the reporting interval needs to be

short enough to measure them with sufficient precision).

The set of rules controlling the determination of each packet's

accountable entity is known as the meter's CURRENT RULE SET. As will

be shown, the meter's current rule set forms an integral part of the

reported information, i.e. the recorded usage information cannot be

properly interpreted without a definition of the rules used to

collect that information.

Settings for these granularity factors may vary from meter to meter.

They are determined by the meter's current rule set, so they will

change if network Operations personnel reconfigure the meter to use a

new rule set. It is expected that the collection rules will change

rather infrequently; nonetheless, the rule set in effect at any time

must be identifiable via a RULE SET ID. Granularity of accountable

entities is further specified by additional ATTRIBUTES. These

attributes include:

- Meter variables such as the index of the flow's record in the flow

table and the rule set id for the rules which the meter was running

while the flow was observed. The values of these attributes

provide a way of distinguishing flows observed by a meter at

different times.

- Attributes which record information derived from other attribute

values. Six of these are defined (SourceClass, DestClass,

FlowClass, SourceKind, DestKind, FlowKind), and their meaning is

determined by the meter's rule set. For example, one could have a

subroutine in the rule set which determined whether a source or

destination peer address was a member of an arbitrary list of

networks, and set SourceClass/DestClass to one if the source/dest

peer address was in the list or to zero otherwise.

- Administratively specified attributes such as Quality Of Service

and Priority, etc. These are not defined at this time.

- Higher-layer (especially application-level) attributes. These are

not defined at this time.

Settings for these granularity factors may vary from meter to meter.

They are determined by the meter's current rule set, so they will

change if network Operations personnel reconfigure the meter to use a

new rule set.

The LIFETIME of a flow is the time interval which began when the

meter observed the first packet belonging to the flow and ended when

it saw the last packet. Flow lifetimes are very variable, but many -

if not most - are rather short. A meter cannot measure lifetimes

directly; instead a meter reader collects usage data for flows which

have been active since the last collection, and an analysis

application may compare the data from each collection so as to

determine when each flow actually stopped.

The meter does, however, need to reclaim memory (i.e. records in the

flow table) being held by idle flows. The meter configuration

includes a variable called InactivityTimeout, which specifies the

minimum time a meter must wait before recovering the flow's record.

In addition, before recovering a flow record the meter must be sure

that the flow's data has been collected by at least one meter reader.

These 'lifetime' issues are considered further in the section on

meter readers (below). A complete list of the attributes currently

defined is given in Appendix C later in this document.

3.3 Rolling Counters, Timestamps, Report-in-One-Bucket-Only

Once an usage record is sent, the decision needs to be made whether

to clear any existing flow records or to maintain them and add to

their counts when recording subsequent traffic on the same flow. The

second method, called rolling counters, is recommended and has

several advantages. Its primary advantage is that it provides

greater reliability - the system can now often survive the loss of

some usage records, such as might occur if a meter reader failed and

later restarted. The next usage record will very often contain yet

another reading of many of the same flow buckets which were in the

lost usage record. The 'continuity' of data provided by rolling

counters can also supply information used for "sanity" checks on the

data itself, to guard against errors in calculations.

The use of rolling counters does introduce a new problem: how to

distinguish a follow-on flow record from a new flow record. Consider

the following example.

CONTINUING FLOW OLD FLOW, then NEW FLOW

start time = 1 start time = 1

Usage record N: flow count = 2000 flow count = 2000 (done)

start time = 1 start time = 5

Usage record N+1: flow count = 3000 new flow count = 1000

Total count: 3000 3000

In the continuing flow case, the same flow was reported when its

count was 2000, and again at 3000: the total count to date is 3000.

In the OLD/NEW case, the old flow had a count of 2000. Its record

was then stopped (perhaps because of temporary idleness, or MAX

LIFETIME policy), but then more traffic with the same characteristics

arrived so a new flow record was started and it quickly reached a

count of 1000. The total flow count from both the old and new

records is 3000.

The flow START TIMESTAMP attribute is sufficient to resolve this. In

the example above, the CONTINUING FLOW flow record in the second

usage record has an old FLOW START timestamp, while the NEW FLOW

contains a recent FLOW START timestamp.

Each packet is counted in one and only one flow, so as to avoid

multiple counting of a single packet. The record of a single flow is

informally called a "bucket." If multiple, sometimes overlapping,

records of usage information are required (aggregate, individual,

etc), the network manager should collect the counts in sufficiently

detailed granularity so that aggregate and combination counts can be

reconstructed in post-processing of the raw usage data.

For example, consider a meter from which it is required to record

both 'total packets coming in interface #1' and 'total packets

arriving from any interface sourced by IP address = a.b.c.d.'

Although a bucket can be declared for each case, it is not clear how

to handle a packet which satisfies both criteria. It must only be

counted once. By default it will be counted in the first bucket for

which it qualifies, and not in the other bucket. Further, it is not

possible to reconstruct this information by post-processing. The

solution in this case is to define not two, but THREE buckets, each

one collecting a unique combination of the two criteria:

Bucket 1: Packets which came in interface 1,

AND were sourced by IP address a.b.c.d

Bucket 2: Packets which came in interface 1,

AND were NOT sourced by IP address a.b.c.d

Bucket 3: Packets which did NOT come in interface 1,

AND were sourced by IP address a.b.c.d

(Bucket 4: Packets which did NOT come in interface 1,

AND NOT sourced by IP address a.b.c.d)

The desired information can now be reconstructed by post-processing.

"Total packets coming in interface 1" can be found by adding buckets

1 & 2, and "Total packets sourced by IP address a.b.c.d" can be found

by adding buckets 1 & 3. Note that in this case bucket 4 is not

explicitly required since its information is not of interest, but it

is supplied here in parentheses for completeness.

4 Meters

A traffic flow meter is a device for collecting data about traffic

flows at a given point within a network; we will call this the

METERING POINT. The header of every packet passing the network

metering point is offered to the traffic meter program.

A meter could be implemented in various ways, including:

- A dedicated small host, connected to a LAN (so that it can see all

packets as they pass by) and running a 'traffic meter' program.

The metering point is the LAN segment to which the meter is

attached.

- A multiprocessing system with one or more network interfaces, with

drivers enabling a traffic meter program to see packets. In this

case the system provides multiple metering points - traffic flows

on any subset of its network interfaces can be measured.

- A packet-forwarding device such as a router or switch. This is

similar to (b) except that every received packet should also be

forwarded, usually on a different interface.

The discussion in the following sections assumes that a meter may

only run a single rule set. It is, however, possible for a meter to

run several rule sets concurrently, matching each packet against

every active rule set and producing a single flow table with flows

from all the active rule sets. The overall effect of doing this

would be similar to running several independent meters, one for each

rule set.

4.1 Meter Structure

An outline of the meter's structure is given in the following

diagram.

Briefly, the meter works as follows:

- Incoming packet headers arrive at the top left of the diagram and

are passed to the PACKET PROCESSOR.

- The packet processor passes them to the Packet Matching Engine

(PME) where they are classified.

- The PME is a Virtual Machine running a pattern matching program

contained in the CURRENT RULE SET. It is invoked by the Packet

Processor, and returns instructions on what to do with the packet.

- Some packets are classified as 'to be ignored.' They are discarded

by the Packet Processor.

- Other packets are matched by the PME, which returns a FLOW KEY

describing the flow to which the packet belongs.

- The flow key is used to locate the flow's entry in the FLOW TABLE;

a new entry is created when a flow is first seen. The entry's

packet and byte counters are updated.

- A meter reader may collect data from the flow table at any time.

It may use the 'collect' index to locate the flows to be collected

within the flow table.

packet +------------------+

header Current Rule Set

+--------+---------+

+--------*---------+ +----------*-------------+

Packet Processor <-----> Packet Matching Engine

+--+------------+--+ +------------------------+

Ignore * Count via flow key

+--*--------------+

'Search' index

+--------+--------+

+--------*--------+

Flow Table

+--------+--------+

+--------*--------+

'Collect' index

+--------+--------+

*

Meter Reader

4.2 Flow Table

Every traffic meter maintains a table of TRAFFIC FLOW RECORDS for

flows seen by the meter. A flow record contains attribute values for

its flow, including:

- Addresses for the flow's source and destination. These include

addresses and masks for various network layers (extracted from the

packet), and the number of the interface on which the packet was

observed.

- First and last times when packets were seen for this flow.

- Counts for 'forward' (source to destination) and 'backward'

(destination to source) components of the flow's traffic.

- Other attributes, e.g. state of the flow record (discussed below).

The state of a flow record may be:

- INACTIVE: The flow record is not being used by the meter.

- CURRENT: The record is in use and describes a flow which belongs to

the 'current flow set,' i.e. the set of flows recently seen by the

meter.

- IDLE: The record is in use and the flow which it describes is part

of the current flow set. In addition, no packets belonging to this

flow have been seen for a period specified by the meter's

InactivityTime variable.

4.3 Packet Handling, Packet Matching

Each packet header received by the traffic meter program is processed

as follows:

- Extract attribute values from the packet header and use them to

create a MATCH KEY for the packet.

- Match the packet's key against the current rule set, as explained

in detail below.

The rule set specifies whether the packet is to be counted or

ignored. If it is to be counted the matching process produces a FLOW

KEY for the flow to which the packet belongs. This flow key is used

to find the flow's record in the flow table; if a record does not yet

exist for this flow, a new flow record may be created. The counts

for the matching flow record can then be incremented.

For example, the rule set could specify that packets to or from any

host in IP network 130.216 are to be counted. It could also specify

that flow records are to be created for every pair of 24-bit (Class

C) subnets within network 130.216.

Each packet's match key is passed to the meter's PATTERN MATCHING

ENGINE (PME) for matching. The PME is a Virtual Machine which uses a

set of instructions called RULES, i.e. a RULE SET is a program for

the PME. A packet's match key contains an interface number, source

address (S) and destination address (D) values. It does not,

however, contain any attribute masks for its attributes, only their

values.

If measured flows were unidirectional, i.e. only counted packets

travelling in one direction, the matching process would be simple.

The PME would be called once to match the packet. Any flow key

produced by a successful match would be used to find the flow's

record in the flow table, and that flow's counters would be updated.

Flows are, however, bidirectional, reflecting the forward and reverse

packets of a protocol interchange or 'session.' Maintaining two sets

of counters in the meter's flow record makes the resulting flow data

much simpler to handle, since analysis programs do not have to gather

together the 'forward' and 'reverse' components of sessions.

Implementing bi-directional flows is, of course, more difficult for

the meter, since it must decide whether a packet is a 'forward'

packet or a 'reverse' one. To make this decision the meter will

often need to invoke the PME twice, once for each possible packet

direction.

The diagram below describes the algorithm used by the traffic meter

to process each packet. Flow through the diagram is from left to

right and top to bottom, i.e. from the top left corner to the bottom

right corner. S indicates the flow's source address (i.e. its set

of source address attribute values) from the packet, and D indicates

its destination address.

There are several cases to consider. These are:

- The packet is recognised as one which is TO BE IGNORED.

- The packet MATCHES IN BOTH DIRECTIONS. One situation in which this

could happen would be a rule set which matches flows within network

X (Source = X, Dest = X) but specifies that flows are to be created

for each subnet within network X, say subnets y and z. If, for

example a packet is seen for y->z, the meter must check that flow

z->y is not already current before creating y->z.

- The packet MATCHES IN ONE DIRECTION ONLY. If its flow is already

current, its forward or reverse counters are incremented.

Otherwise it is added to the flow table and then counted.

The algorithm uses four functions, as follows:

match(A->B) implements the PME. It uses the meter's current rule set

to match the attribute values in the packet's match key. A->B means

that the assumed source address is A and destination address B, i.e.

that the packet was travelling from A to B. match() returns one of

three results:

'Ignore' means that the packet was matched but this flow is not

to be counted.

'Fail' means that the packet did not match. It might, however

match with its direction reversed, i.e. from B to A.

'Suc' means that the packet did match, i.e. it belongs to a flow

which is to be counted.

current(A->B) succeeds if the flow A-to-B is current - i.e. has

a record in the flow table whose state is Current - and fails

otherwise.

create(A->B) adds the flow A-to-B to the flow table, setting the

value for attributes - such as addresses - which remain constant,

and zeroing the flow's counters.

count(A->B,f) increments the 'forward' counters for flow A-to-B.

count(A->B,r) increments the 'reverse' counters for flow A-to-B.

'Forward' here means the counters for packets travelling from

A to B. Note that count(A->B,f) is identical to count(B->A,r).

Ignore

--- match(S->D) -------------------------------------------------+

Suc Fail

Ignore

match(D->S) -----------------------------------------+

Suc Fail

+-------------------------------------------+

Suc

current(D->S) ---------- count(D->S,r) --------------+

Fail

create(D->S) ----------- count(D->S,r) --------------+

Suc

current(S->D) ------------------ count(S->D,f) --------------+

Fail

Suc

current(D->S) ------------------ count(D->S,r) --------------+

Fail

create(S->D) ------------------- count(S->D,f) --------------+

*

When writing rule sets one must remember that the meter will normally

try to match each packet in both directions. It is particularly

important that the rule set does not contain inconsistencies which

will upset this process.

Consider, for example, a rule set which counts packets from source

network A to destination network B, but which ignores packets from

source network B. This is an obvious example of an inconsistent rule

set, since packets from network B should be counted as reverse

packets for the A-to-B flow.

This problem could be avoided by devising a language for specifying

rule files and writing a compiler for it, thus making it much easier

to produce correct rule sets. Another approach would be to write a

'rule set consistency checker' program, which could detect problems

in hand-written rule sets.

In the short term the best way to avoid these problems is to write

rule sets which only clasify flows in the forward direction, and rely

on the meter to handle reverse-travelling packets.

4.4 Rules and Rule Sets

A rule set is an array of rules. Rule sets are held within a meter

as entries in an array of rule sets. One member of this array is the

CURRENT RULE SET, in that it is the one which is currently being used

by the meter to classify incoming packets.

Rule set 1 is built in to the meter and cannot be changed. It is run

when the meter is started up, and provides a very coarse reporting

granularity; it is mainly useful for verifying that the meter is

running, before a 'useful' rule set is downloaded to it.

If the meter is instructed to use rule set 0, it will cease

measuring; all packets will be ignored until another (non-zero) rule

set is made current.

Each rule in a rule set is structured as follows:

+-------- test ---------+ +---- action -----+

attribute & mask = value: opcode, parameter;

Opcodes contain two flags: 'goto' and 'test.' The PME maintains a

Boolean indicator called the 'test indicator,' which is initially set

(on). Execution begins with rule 1, the first in the rule set. It

proceeds as follows:

If the test indicator is on:

Perform the test, i.e. AND the attribute value with the

mask and compare it with the value.

If these are equal the test has succeeded; perform the

rule's action (below).

If the test fails execute the next rule in the rule set.

If there are no more rules in the rule set, return from the

match() function indicating failure.

If the test indicator is off, or the test (above) succeeded:

Set the test indicator to this rule's test flag value.

Determine the next rule to execute.

If the opcode has its goto flag set, its parameter value

specifies the number of the next rule.

Opcodes which don't have their goto flags set either

determine the next rule in special ways (Return),

or they terminate execution (Ignore, Fail, Count,

CountPkt).

Perform the action.

The PME maintains two 'history' data structures. The first, the

'return' stack, simply records the index (i.e. 1-origin rule number)

of each Gosub rule as it is executed; Return rules pop their Gosub

rule index. The second, the 'pattern' queue, is used to save

information for later use in building a flow key. A flow key is

built by zeroing all its attribute values, then copying attribute and

mask information from the pattern stack in the order it was enqueued.

The opcodes are:

opcode goto test

1 Ignore 0 -

2 Fail 0 -

3 Count 0 -

4 CountPkt 0 -

5 Return 0 0

6 Gosub 1 1

7 GosubAct 1 0

8 Assign 1 1

9 AssignAct 1 0

10 Goto 1 1

11 GotoAct 1 0

12 PushRuleTo 1 1

13 PushRuleToAct 1 0

14 PushPktTo 1 1

15 PushPktToAct 1 0

The actions they perform are:

Ignore: Stop matching, return from the match() function

indicating that the packet is to be ignored.

Fail: Stop matching, return from the match() function

indicating failure.

Count: Stop matching. Save this rule's attribute name,

mask and value in the PME's pattern queue, then

construct a flow key for the flow to which this

this packet belongs. Return from the match()

function indicating success. The meter will use

the flow key to locate the flow record for this

packet's flow.

CountPkt: As for Count, except that the masked value from

the packet is saved in the PME's pattern queue

instead of the rule's value.

Gosub: Call a rule-matching subroutine. Push the current

rule number on the PME's return stack, set the

test indicator then goto the specified rule.

GosubAct: Same as Gosub, except that the test indicator is

cleared before going to the specified rule.

Return: Return from a rule-matching subroutine. Pop the

number of the calling gosub rule from the PME's

'return' stack and add this rule's parameter value

to it to determine the 'target' rule. Clear the

test indicator then goto the target rule.

A subroutine call appears in a rule set as a Gosub

rule followed by a small group of following rules.

Since a Return action clears the test flag, the

action of one of these 'following' rules will be

executed; this allows the subroutine to return a

result (in addition to any information it may save

in the PME's pattern queue).

Assign: Set the attribute specified in this rule to the

value specified in this rule. Set the test

indicator then goto the specified rule.

AssignAct: Same as Assign, except that the test indicator

is cleared before going to the specified rule.

Goto: Set the test indicator then goto the

specified rule.

GotoAct: Clear the test indicator then goto the specified

rule.

PushRuleTo: Save this rule's attribute name, mask and value

in the PME's pattern queue. Set the test

indicator then goto the specified rule.

PushRuleToAct: Same as PushRuleTo, except that the test indicator

is cleared before going to the specified rule.

PushRuleTo actions may be used to save the value

and mask used in a test, or (if the test is not

performed) to save an arbitrary value and mask.

PushPktTo: Save this rule's attribute name, mask, together

with the masked value from the packet, in the

PME's pattern queue. SET the test indicator then

goto the specified rule.

PushPktToAct: Same as PushPktTo, except that the test indicator

is cleared before going to the specified rule.

PushPktTo actions may be used to save a value from

the packet using a specified mask. The test in

PushPktTo rules will almost never be executed.

As well as the attributes applying directly to packets (such as

SourcePeerAddress, DestTransAddress, etc.) the PME implements

several further attribtes. These are:

Null: Tests performed on the Null attribute always succeed.

v1 .. v5: v1, v2, v3, v4 and v5 are 'meter variables.' They

provide a way to pass parameters into rule-matching

subroutines. Each may hold the name of a normal

attribute; its value is set by an Assign action.

When a meter variable appears as the attribute of a

rule, its value specifies the actual attribute to be

tested. For example, if v1 had been assigned

SourcePeerAddress as its value, a rule with v1 as its

attribute would actually test SourcePeerAddress.

SourceClass, DestClass, FlowClass,

SourceKind, DestKind, FlowKind:

These six attributes may be set by executing PushRuleto

actions. They allow the PME to save (in flow records)

information which has been built up during matching.

Since their values are only defined when matching is

complete (and the flow key is built) their values may

not be tested in rules.

4.5 Maintaining the Flow Table

The flow table may be thought of as a 1-origin array of flow records.

(A particular implementation may, of course, use whatever data

structure is most suitable). When the meter starts up there are no

known flows; all the flow records are in the 'inactive' state.

Each time a packet is seen for a flow which is not in the current

flow set a flow record is set up for it; the state of such a record

is 'current.' When selecting a record for the new flow the meter

searches the flow table for a 'inactive' record - there is no

particular significance in the ordering of records within the table.

Flow data may be collected by a 'meter reader' at any time. There is

no requirement for collections to be synchronized. The reader may

collect the data in any suitable manner, for example it could upload

a copy of the whole flow table using a file transfer protocol, or it

could read the records in the current flow set row by row using a

suitable data transfer protocol.

The meter keeps information about collections, in particular it

maintains a LastCollectTime variable which remembers the time the

last collection was made. A second variable, InactivityTime,

specifies the minimum time the meter will wait before considering

that a flow is idle.

The meter must recover records used for idle flows, if only to

prevent it running out of flow records. Recovered flow records are

returned to the 'inactive' state. A variety of recovery strategies

are possible, including the following:

One possible recovery strategy is to recover idle flow records as

soon as possible after their data has been collected. To implement

this the meter could run a background process which scans the flow

table looking for 'current' flows whose 'last packet' time is earlier

than the meter's LastCollectTime. This would be suitable for use

when one was interested in measuring flow lifetimes.

Another recovery strategy is to leave idle flows alone as long as

possible, which would be suitable if one was only interested in

measuring total traffic volumes. It could be implemented by having

the meter search for collected idle flows only when it ran out of

'inactive' flow records.

One further factor a meter should consider before recovering a flow

is the number of meter readers which have collected the flow's data.

If there are multiple meter readers operating, network Operations

personnel should be able to specify the minimum number of meters - or

perhaps a specific list of meters - which should collect a flow's

data before its memory can be recovered. This issue will be further

developed in the future.

4.6 Handling Increasing Traffic Levels

Under normal conditions the meter reader specifies which set of usage

records it wants to collect, and the meter provides them.

If memory usage rises above the high-water mark the meter should

switch to a STANDBY RULE SET so as to increase the granularity of

flow collection and decrease the rate at which new flows are created.

When the manager, usually as part of a regular poll, becomes aware

that the meter is using its standby rule set, it could decrease the

interval between collections. The meter should also increase its

efforts to recover flow memory so as to reduce the number of idle

flows in memory. When the situation returns to normal, the manager

may request the meter to switch back to its normal rule set.

5 Meter Readers

Usage data is accumulated by a meter (e.g. in a router) as memory

permits. It is collected at regular reporting intervals by meter

readers, as specified by a manager. The collected data is recorded

in a disk file called a FLOW DATA FILE, as a sequence of USAGE

RECORDS.

The following sections describe the contents of usage records and

flow data files. Note, however, that at this stage the details of

such records and files is not specified in the architecture.

Specifying a common format for them would be a worthwhile future

development.

5.1 Identifying Flows in Flow Records

Once a packet has been classified and is ready to be counted, an

appropriate flow data record must already exist in the flow table;

otherwise one must be created. The flow record has a flexible format

where unnecessary identification attributes may be omitted. The

determination of which attributes of the flow record to use, and of

what values to put in them, is specified by the current rule set.

Note that the combination of start time, rule set id and subscript

(row number in the flow table) provide a unique flow identifier,

regardless of the values of its other attributes.

The current rule set may specify additional information, e.g. a

computed attribute value such as FlowKind, which is to be placed in

the attribute section of the usage record. That is, if a particular

flow is matched by the rule set, then the corresponding flow record

should be marked not only with the qualifying identification

attributes, but also with the additional information. Using this

feature, several flows may each carry the same FlowKind value, so

that the resulting usage records can be used in post-processing or

between meter reader and meter as a criterion for collection.

5.2 Usage Records, Flow Data Files

The collected usage data will be stored in flow data files on the

meter reader, one file for each meter. As well as containing the

measured usage data, flow data files must contain information

uniquely identifiying the meter from which it was collected.

A USAGE RECORD contains the descriptions of and values for one or

more flows. Quantities are counted in terms of number of packets and

number of bytes per flow. Each usage record contains the entity

identifier of the meter (a network address), a time stamp and a list

of reported flows (FLOW DATA RECORDS). A meter reader will build up a

file of usage records by regularly collecting flow data from a meter,

using this data to build usage records and concatenating them to the

tail of a file. Such a file is called a FLOW DATA FILE.

A usage record contains the following information in some form:

+-------------------------------------------------------------------+

RECORD IDENTIFIERS:

Meter Id (& digital signature if required)

Timestamp

Collection Rules ID

+-------------------------------------------------------------------+

FLOW IDENTIFIERS: COUNTERS

Address List Packet Count

Subscriber ID (Optional) Byte Count

Attributes (Optional) Flow Start/Stop Time

+-------------------------------------------------------------------+

5.3 Meter to Meter Reader: Usage Record Transmission

The usage record contents are the raison d'etre of the system. The

accuracy, reliability, and security of transmission are the primary

concerns of the meter/meter reader exchange. Since errors may occur

on networks, and Internet packets may be dropped, some mechanism for

ensuring that the usage information is transmitted intact is needed.

Flow data is moved from meter to meter reader via a series of

protocol exchanges between them. This may be carried out in various

ways, moving individual attribute values, complete flows, or the

entire flow table (i.e. all the active flows). One possible method

of achieving this transfer is to use SNMP; the 'Traffic Flow

Measurement: Meter MIB' document [4] gives details. Note that this

is simply one example; the transfer of flow data from meter to meter

reader is not specified in this document.

The reliability of the data transfer method under light, normal, and

extreme network loads should be understood before selecting among

collection methods.

In normal operation the meter will be running a rule file which

provides the required degree of flow reporting granularity, and the

meter reader(s) will collect the flow data often enough to allow the

meter's garbage collection mechanism to maintain a stable level of

memory usage.

In the worst case traffic may increase to the point where the meter

is in danger of running completely out of flow memory. The meter

implementor must decide how to handle this, for example by switching

to a default (extremely coarse granularity) rule set, by sending a

trap to the manager, or by attempting to dump flow data to the meter

reader.

Users of the Traffic Flow Measurement system should analyse their

requirements carefully and assess for themselves whether it is more

important to attempt to collect flow data at normal granularity

(increasing the collection frequency as needed to keep up with

traffic volumes), or to accept flow data with a coarser granularity.

Similarly, it may be acceptable to lose flow data for a short time in

return for being sure that the meter keeps running properly, i.e. is

not overwhelmed by rising traffic levels.

6 Managers

A manager configures meters and controls meter readers. It does this

via the interactions described below.

6.1 Between Manager and Meter: Control Functions

- DOWNLOAD RULE SET: A meter may hold an array of rule sets. One of

these, the 'default' rule set, is built in to the meter and cannot

be changed; the others must be downloaded by the manager. A

manager may use any suitable protocol exchange to achieve this, for

example an FTP file transfer or a series of SNMP SETs, one for each

row of the rule set.

- SWITCH TO SPECIFIED RULE SET: Once the rule sets have been

downloaded, the manager must instruct the meter which rule set it

is to actually run (i.e. which is to be the current rule set), and

which is to be the standby rule set.

- SET HIGH WATER MARK: A percentage value interpreted by the meter

which tells the meter when to switch to its standby rule set, so as

to increase the granularity of the flows and conserve the meter's

flow memory. Once this has happened, the manager may also change

the polling frequency or the meter's control parameters (so as to

increase the rate at which the meter can recover memory from idle

flows).

If the high traffic levels persist, the meter's normal rule set may

have to be rewritten to permanently reduce the reporting

granularity.

- SET FLOW TERMINATION PARAMETERS: The meter should have the good

sense in situations where lack of resources may cause data loss to

purge flow records from its tables. Such records may include:

- Flows that have already been reported to at least one meter

reader, and show no activity since the last report,

- Oldest flows, or

- Flows with the smallest number of unreported packets.

- SET INACTIVITY TIMEOUT: This is a time in seconds since the last

packet was seen for a flow. Flow records may be reclaimed if they

have been idle for at least this amount of time, and have been

collected in accordance with the current collection criteria.

6.2 Between Manager and Meter Reader: Control Functions

Because there are a number of parameters that must be set for traffic

flow measurement to function properly, and viable settings may change

as a result of network traffic characteristics, it is desirable to

have dynamic network management as opposed to static meter

configurations. Many of these operations have to do with space

tradeoffs - if memory at the meter is exhausted, either the reporting

interval must be decreased or a coarser granularity of aggregation

must be used so that more data fits into less space.

Increasing the reporting interval effectively stores data in the

meter; usage data in transit is limited by the effective bandwidth of

the virtual link between the meter and the meter reader, and since

these limited network resources are usually also used to carry user

data (the purpose of the network), the level of traffic flow

measurement traffic should be kept to an affordable fraction of the

bandwidth. ("Affordable" is a policy decision made by the network

Operations personnel). At any rate, it must be understood that the

operations below do not represent the setting of independent

variables; on the contrary, each of the values set has a direct and

measurable effect on the behaviour of the other variables.

Network management operations follow:

- MANAGER and METER READER IDENTIFICATION: The manager should ensure

that meters report to the correct set of collection stations, and

take steps to prevent unauthorised access to usage information.

The collection stations so identified should be prepared to poll if

necessary and accept data from the appropriate meters. Alternate

collection stations may be identified in case both the primary

manager and the primary collection station are unavailable.

Similarly, alternate managers may be identified.

- REPORTING INTERVAL CONTROL: The usual reporting interval should be

selected to cope with normal traffic patterns. However, it may be

possible for a meter to exhaust its memory during traffic spikes

even with a correctly set reporting interval. Some mechanism must

be available for the meter to tell the manager that it is in danger

of exhausting its memory (by declaring a 'high water' condition),

and for the manager to arbitrate (by decreasing the polling

interval, letting nature take its course, or by telling the meter

to ask for help sooner next time).

- GRANULARITY CONTROL: Granularity control is a catch-all for all the

parameters that can be tuned and traded to optimise the system's

ability to reliably measure and store information on all the

traffic (or as close to all the traffic as an administration

requires). Granularity

- Controls flow-id granularities for each interface, and

- Determines the number of buckets into which user traffic will

be lumped together.

Since granularity is controlled by the meter's current rule set,

the manager can only change it by requesting the meter to switch to

a different rule set. The new rule set could be downloaded when

required, or it could have been downloaded as part of the meter's

initial configuration.

- FLOW LIFETIME CONTROL: Flow termination parameters include timeout

parameters for obsoleting inactive flows and removing them from

tables and maximum flow lifetimes. This is intertwined with

reporting interval and granularity, and must be set in accordance

with the other parameters.

6.3 Exception Conditions

Exception conditions must be handled, particularly occasions when the

meter runs out of buffer space. Since, to prevent counting any

packet twice, packets can only be counted in a single flow at any

given time, discarding records will result in the loss of

information. The mechanisms to deal with this are as follows:

- METER OUTAGES: In case of impending meter outages (controlled

crashes, etc.) the meter could send a trap to the manager. The

manager could then request one or more meter readers to pick up the

usage record from the meter.

Following an uncontrolled meter outage such as a power failure, the

meter could send a trap to the manager indicating that it has

restarted. The manager could then download the meter's correct

rule set and advise the meter reader(s) that the meter is running

again. Alternatively, the meter reader may discover from its

regular poll that a meter has failed and restarted. It could then

advise the manager of this, instead of relying on a trap from the

meter.

- METER READER OUTAGES: If the collection system is down or isolated,

the meter should try to inform the manager of its failure to

communicate with the collection system. Usage data is maintained

in the flows' rolling counters, and can be recovered when the meter

reader is restarted.

- MANAGER OUTAGES: If the manager fails for any reason, the meter

should continue measuring and the meter reader(s) should keep

gathering usage records.

- BUFFER PROBLEMS: The network manager may realise that there is a

'low memory' condition in the meter. This can usually be

attributed to the interaction between the following controls:

- The reporting interval is too infrequent,

- The reporting granularity is too fine, or

- The throughput/bandwidth of circuits carrying the usage

data is too low.

The manager may change any of these parameters in response to the

meter (or meter reader's) plea for help.

6.4 Standard Rule Sets

Although the rule table is a flexible tool, it can also become very

complex. It may be helpful to develop some rule sets for common

applications:

- PROTOCOL TYPE: The meter records packets by protocol type. This

will be the default rule table for Traffic Flow Meters.

- ADJACENT SYSTEMS: The meter records packets by the MAC address of

the Adjacent Systems (neighbouring originator or next-hop).

(Variants on this table are "report source" or "report sink" only.)

This strategy might be used by a regional or backbone network which

wants to know how much aggregate traffic flows to or from its

subscriber networks.

- END SYSTEMS: The meter records packets by the IP address pair

contained in the packet. (Variants on this table are "report

source" or "report sink" only.) This strategy might be used by an

End System network to get detailed host traffic matrix usage data.

- TRANSPORT TYPE: The meter records packets by transport address; for

IP packets this provides usage information for the various IP

services.

- HYBRID SYSTEMS: Combinations of the above, e.g. for one interface

report End Systems, for another interface report Adjacent Systems.

This strategy might be used by an enterprise network to learn

detail about local usage and use an aggregate count for the shared

regional network.

7 APPENDICES

7.1 Appendix A: Network Characterisation

Internet users have extraordinarily diverse requirements. Networks

differ in size, speed, throughput, and processing power, among other

factors. There is a range of traffic flow measurement capabilities

and requirements. For traffic flow measurement purposes, the

Internet may be viewed as a continuum which changes in character as

traffic passes through the following representative levels:

International

Backbones/National ---------------

/ Regional/MidLevel ---------- ----------

/ \ \ / / Stub/Enterprise --- --- --- ---- ----

End-Systems/Hosts xxx xxx xxx xxxx xxxx

Note that mesh architectures can also be built out of these

components, and that these are merely descriptive terms. The nature

of a single network may encompass any or all of the descriptions

below, although some networks can be clearly identified as a single

type.

BACKBONE networks are typically bulk carriers that connect other

networks. Individual hosts (with the exception of network management

devices and backbone service hosts) typically are not directly

connected to backbones.

REGIONAL networks are closely related to backbones, and differ only

in size, the number of networks connected via each port, and

geographical coverage. Regionals may have directly connected hosts,

acting as hybrid backbone/stub networks. A regional network is a

SUBSCRIBER to the backbone.

STUB/ENTERPRISE networks connect hosts and local area networks.

STUB/ENTERPRISE networks are SUBSCRIBERS to regional and backbone

networks.

END SYSTEMS, colloquially HOSTS, are SUBSCRIBERS to any of the above

networks.

Providing a uniform identification of the SUBSCRIBER in finer

granularity than that of end-system, (e.g. user/account), is beyond

the scope of the current architecture, although an optional attribute

in the traffic flow measurement record may carry system-specific

"accountable (billable) party" labels so that meters can implement

proprietary or non-standard schemes for the attribution of network

traffic to responsible parties.

7.2 Appendix B: Recommended Traffic Flow Measurement Capabilities

Initial recommended traffic flow measurement conventions are outlined

here according to the following Internet building blocks. It is

important to understand what complexity reporting introduces at each

network level. Whereas the hierarchy is described top-down in the

previous section, reporting requirements are more easily addressed

bottom-up.

End-Systems

Stub Networks

Enterprise Networks

Regional Networks

Backbone Networks

END-SYSTEMS are currently responsible for allocating network usage to

end-users, if this capability is desired. From the Internet Protocol

perspective, end-systems are the finest granularity that can be

identified without protocol modifications. Even if a meter violated

protocol boundaries and tracked higher-level protocols, not all

packets could be correctly allocated by user, and the definition of

user itself varies too widely from operating system to operating

system (e.g. how to trace network usage back to users from shared

processes).

STUB and ENTERPRISE networks will usually collect traffic data either

by end- system network address or network address pair if detailed

reporting is required in the local area network. If no local

reporting is required, they may record usage information in the exit

router to track external traffic only. (These are the only networks

which routinely use attributes to perform reporting at granularities

finer than end-system or intermediate-system network address.)

REGIONAL networks are intermediate networks. In some cases,

subscribers will be enterprise networks, in which case the

intermediate system network address is sufficient to identify the

regional's immediate subscriber. In other cases, individual hosts or

a disjoint group of hosts may constitute a subscriber. Then end-

system network address pairs need to be tracked for those

subscribers. When the source may be an aggregate entity (such as a

network, or adjacent router representing traffic from a world of

hosts beyond) and the destination is a singular entity (or vice

versa), the meter is said to be operating as a HYBRID system.

At the regional level, if the overhead is tolerable it may be

advantageous to report usage both by intermediate system network

address (e.g. adjacent router address) and by end-system network

address or end-system network address pair.

BACKBONE networks are the highest level networks operating at higher

link speeds and traffic levels. The high volume of traffic will in

most cases preclude detailed traffic flow measurement. Backbone

networks will usually account for traffic by adjacent routers'

network addresses.

7.3 Appendix C: List of Defined Flow Attributes

This Appendix provides a checklist of the attributes defined to date;

others will be added later as the Traffic Measurement Architecture is

further developed.

0 Null

1 Flow Subscript Integer Flow table info

2 Flow Status Integer

4 Source Interface Integer Source Address

5 Source Adjacent Type Integer

6 Source Adjacent Address String

7 Source Adjacent Mask String

8 Source Peer Type Integer

9 Source Peer Address String

10 Source Peer Mask String

11 Source Trans Type Integer

12 Source Trans Address String

13 Source Trans Mask String

14 Destination Interface Integer Destination Address

15 Destination Adjacent Type Integer

16 Destination Adjacent Address String

17 Destination AdjacentMask String

18 Destination PeerType Integer

19 Destination PeerAddress String

20 Destination PeerMask String

21 Destination TransType Integer

22 Destination TransAddress String

23 Destination TransMask String

24 Packet Scale Factor Integer 'Other' attributes

25 Byte Scale Factor Integer

26 Rule Set Number Integer

27 Forward Bytes Counter Source-to-Dest counters

28 Forward Packets Counter

29 Reverse Bytes Counter Dest-to-Source counters

30 Reverse Packets Counter

31 First Time TimeTicks Activity times

32 Last Active Time TimeTicks

33 Source Subscriber ID String Session attributes

34 Destination Subscriber ID String

35 Session ID String

36 Source Class Integer 'Computed' attributes

37 Destination Class Integer

38 Flow Class Integer

39 Source Kind Integer

40 Destination Kind Integer

41 Flow Kind Integer

51 V1 Integer Meter variables

52 V2 Integer

53 V3 Integer

54 V4 Integer

55 V5 Integer

7.4 Appendix D: List of Meter Control Variables

Current Rule Set Number Integer

Standby Rule Set Number Integer

High Water Mark Percentage

Flood Mark Percentage

Inactivity Timeout (seconds) Integer

Last Collect Time TimeTicks

8 Acknowledgments

This document was initially produced under the auspices of the IETF's

Internet Accounting Working Group with assistance from SNMP, RMON and

SAAG working groups. This version documents the implementation work

done by the Internet Accounting Working Group, and is intended to

provide a starting point for the Realtime Traffic Flow Measurement

Working Group. Particular thanks are due to Stephen Stibler (IBM

Research) for his patient and careful comments during the preparation

of this memo.

9 References

[1] Mills, C., Hirsch, G. and G. Ruth, "Internet Accounting

Background", RFC1272, Bolt Beranek and Newman Inc., Meridian

Technology Corporation, November 1991.

[2] International Standards Organisation (ISO), "Management

Framework," Part 4 of Information Processing Systems Open

Systems Interconnection Basic Reference Model, ISO 7498-4,

1994.

[3] IEEE 802.3/ISO 8802-3 Information Processing Systems -

Local Area Networks - Part 3: Carrier sense multiple access

with collision detection (CSMA/CD) access method and physical

layer specifications, 2nd edition, September 21, 1990.

[4] Brownlee, N., "Traffic Flow Measurement: Meter MIB",

RFC2064, The University of Auckland, January 1997.

10 Security Considerations

Security issues are not discussed in detail in this document. The

meter's management and collection protocols are responsible for

providing sufficient data integrity and confidentiality.

11 Authors' Addresses

Nevil Brownlee

Information Technology Systems & Services

The University of Auckland

Phone: +64 9 373 7599 x8941

EMail: n.brownlee @auckland.ac.nz

Cyndi Mills

BBN Systems and Technologies

Phone: +1 617 873 4143

EMail: cmills@bbn.com

Greg Ruth

GTE Laboratories, Inc

Phone: +1 617 466 2448

EMail: gruth@gte.com

 
 
 
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