path: root/doc/rfc/rfc3290.txt

Network Working Group                                          Y. Bernet
Request for Comments: 3290                                     Microsoft
Category: Informational                                         S. Blake
                                                                Ericsson
                                                             D. Grossman
                                                                Motorola
                                                                A. Smith
                                                        Harbour Networks
                                                                May 2002


           An Informal Management Model for Diffserv Routers

Status of this Memo

   This memo provides information for the Internet community.  It does
   not specify an Internet standard of any kind.  Distribution of this
   memo is unlimited.

Copyright Notice

   Copyright (C) The Internet Society (2002).  All Rights Reserved.

Abstract

   This document proposes an informal management model of Differentiated
   Services (Diffserv) routers for use in their management and
   configuration.  This model defines functional datapath elements
   (e.g., classifiers, meters, actions, marking, absolute dropping,
   counting, multiplexing), algorithmic droppers, queues and schedulers.
   It describes possible configuration parameters for these elements and
   how they might be interconnected to realize the range of traffic
   conditioning and per-hop behavior (PHB) functionalities described in
   the Diffserv Architecture.

Table of Contents

   1 Introduction .................................................    3
   2 Glossary .....................................................    4
   3 Conceptual Model .............................................    7
   3.1 Components of a Diffserv Router ............................    7
   3.1.1 Datapath .................................................    7
   3.1.2 Configuration and Management Interface ...................    9
   3.1.3 Optional QoS Agent Module ................................   10
   3.2 Diffserv Functions at Ingress and Egress ...................   10
   3.3 Shaping and Policing .......................................   12
   3.4 Hierarchical View of the Model .............................   12
   4 Classifiers ..................................................   13



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   4.1 Definition .................................................   13
   4.1.1 Filters ..................................................   15
   4.1.2 Overlapping Filters ......................................   15
   4.2 Examples ...................................................   16
   4.2.1 Behavior Aggregate (BA) Classifier .......................   16
   4.2.2 Multi-Field (MF) Classifier ..............................   17
   4.2.3 Free-form Classifier .....................................   17
   4.2.4 Other Possible Classifiers ...............................   18
   5 Meters .......................................................   19
   5.1 Examples ...................................................   20
   5.1.1 Average Rate Meter .......................................   20
   5.1.2 Exponential Weighted Moving Average (EWMA) Meter .........   21
   5.1.3 Two-Parameter Token Bucket Meter .........................   21
   5.1.4 Multi-Stage Token Bucket Meter ...........................   22
   5.1.5 Null Meter ...............................................   23
   6 Action Elements ..............................................   23
   6.1 DSCP Marker ................................................   24
   6.2 Absolute Dropper ...........................................   24
   6.3 Multiplexor ................................................   25
   6.4 Counter ....................................................   25
   6.5 Null Action ................................................   25
   7 Queuing Elements .............................................   25
   7.1 Queuing Model ..............................................   26
   7.1.1 FIFO Queue ...............................................   27
   7.1.2 Scheduler ................................................   28
   7.1.3 Algorithmic Dropper ......................................   30
   7.2 Sharing load among traffic streams using queuing ...........   33
   7.2.1 Load Sharing .............................................   34
   7.2.2 Traffic Priority .........................................   35
   8 Traffic Conditioning Blocks (TCBs) ...........................   35
   8.1 TCB ........................................................   36
   8.1.1 Building blocks for Queuing ..............................   37
   8.2 An Example TCB .............................................   37
   8.3 An Example TCB to Support Multiple Customers ...............   42
   8.4 TCBs Supporting Microflow-based Services ...................   44
   8.5 Cascaded TCBs ..............................................   47
   9 Security Considerations ......................................   47
   10 Acknowledgments .............................................   47
   11 References ..................................................   47
   Appendix A. Discussion of Token Buckets and Leaky Buckets ......   50
   Authors' Addresses .............................................   55
   Full Copyright Statement........................................   56









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1.  Introduction

   Differentiated Services (Diffserv) [DSARCH] is a set of technologies
   which allow network service providers to offer services with
   different kinds of network quality-of-service (QoS) objectives to
   different customers and their traffic streams.  This document uses
   terminology defined in [DSARCH] and [NEWTERMS] (some of these
   definitions are included here in Section 2 for completeness).

   The premise of Diffserv networks is that routers within the core of
   the network handle packets in different traffic streams by forwarding
   them using different per-hop behaviors (PHBs).  The PHB to be applied
   is indicated by a Diffserv codepoint (DSCP) in the IP header of each
   packet [DSFIELD].  The DSCP markings are applied either by a trusted
   upstream node, e.g., a customer, or by the edge routers on entry to
   the Diffserv network.

   The advantage of such a scheme is that many traffic streams can be
   aggregated to one of a small number of behavior aggregates (BA),
   which are each forwarded using the same PHB at the router, thereby
   simplifying the processing and associated storage.  In addition,
   there is no signaling other than what is carried in the DSCP of each
   packet, and no other related processing that is required in the core
   of the Diffserv network since QoS is invoked on a packet-by-packet
   basis.

   The Diffserv architecture enables a variety of possible services
   which could be deployed in a network.  These services are reflected
   to customers at the edges of the Diffserv network in the form of a
   Service Level Specification (SLS - see [NEWTERMS]).  Whilst further
   discussion of such services is outside the scope of this document
   (see [PDBDEF]), the ability to provide these services depends on the
   availability of cohesive management and configuration tools that can
   be used to provision and monitor a set of Diffserv routers in a
   coordinated manner.  To facilitate the development of such
   configuration and management tools it is helpful to define a
   conceptual model of a Diffserv router that abstracts away
   implementation details of particular Diffserv routers from the
   parameters of interest for configuration and management.  The purpose
   of this document is to define such a model.

   The basic forwarding functionality of a Diffserv router is defined in
   other specifications; e.g., [DSARCH, DSFIELD, AF-PHB, EF-PHB].

   This document is not intended in any way to constrain or to dictate
   the implementation alternatives of Diffserv routers.  It is expected
   that router implementers will demonstrate a great deal of variability
   in their implementations.  To the extent that implementers are able



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   to model their implementations using the abstractions described in
   this document, configuration and management tools will more readily
   be able to configure and manage networks incorporating Diffserv
   routers of assorted origins.

   This model is intended to be abstract and capable of representing the
   configuration parameters important to Diffserv functionality for a
   variety of specific router implementations.  It is not intended as a
   guide to system implementation nor as a formal modeling description.
   This model serves as the rationale for the design of an SNMP MIB
   [DSMIB] and for other configuration interfaces (e.g., other policy-
   management protocols) and, possibly, more detailed formal models
   (e.g., [QOSDEVMOD]): these should all be consistent with this model.

   o  Section 3 starts by describing the basic high-level blocks of a
      Diffserv router.  It explains the concepts used in the model,
      including the hierarchical management model for these blocks which
      uses low-level functional datapath elements such as Classifiers,
      Actions, Queues.

   o  Section 4 describes Classifier elements.

   o  Section 5 discusses Meter elements.

   o  Section 6 discusses Action elements.

   o  Section 7 discusses the basic queuing elements of Algorithmic
      Droppers, Queues, and Schedulers and their functional behaviors
      (e.g., traffic shaping).

   o  Section 8 shows how the low-level elements can be combined to
      build modules called Traffic Conditioning Blocks (TCBs) which are
      useful for management purposes.

   o  Section 9 discusses security concerns.

   o  Appendix A contains a brief discussion of the token bucket and
      leaky bucket algorithms used in this model and some of the
      practical effects of the use of token buckets within the Diffserv
      architecture.

2.  Glossary

   This document uses terminology which is defined in [DSARCH].  There
   is also current work-in-progress on this terminology in the IETF and
   some of the definitions provided here are taken from that work.  Some





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   of the terms from these other references are defined again here in
   order to provide additional detail, along with some new terms
   specific to this document.

   Absolute      A functional datapath element which simply discards all
   Dropper       packets arriving at its input.

   Algorithmic   A functional datapath element which selectively
   Dropper       discards packets that arrive at its input, based on a
                 discarding algorithm.  It has one data input and one
                 output.

   Classifier    A functional datapath element which consists of filters
                 that select matching and non-matching packets.  Based
                 on this selection, packets are forwarded along the
                 appropriate datapath within the router.  A classifier,
                 therefore, splits a single incoming traffic stream into
                 multiple outgoing streams.

   Counter       A functional datapath element which updates a packet
                 counter and also an octet counter for every
                 packet that passes through it.

   Datapath      A conceptual path taken by packets with particular
                 characteristics through a Diffserv router.  Decisions
                 as to the path taken by a packet are made by functional
                 datapath elements such as Classifiers and Meters.

   Filter        A set of wildcard, prefix, masked, range and/or exact
                 match conditions on the content of a packet's
                 headers or other data, and/or on implicit or derived
                 attributes associated with the packet.  A filter is
                 said to match only if each condition is satisfied.

   Functional    A basic building block of the conceptual router.
   Datapath      Typical elements are Classifiers, Meters, Actions,
   Element       Algorithmic Droppers, Queues and Schedulers.

   Multiplexer   A multiplexor.
   (Mux)

   Multiplexor   A functional datapath element that merges multiple
   (Mux)         traffic streams (datapaths) into a single traffic
                 stream (datapath).







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   Non-work-     A property of a scheduling algorithm such that it
   conserving    services packets no sooner than a scheduled departure
                 time, even if this means leaving packets queued
                 while the output (e.g., a network link or connection
                 to the next element) is idle.

   Policing      The process of comparing the arrival of data packets
                 against a temporal profile and forwarding, delaying
                 or dropping them so as to make the output stream
                 conformant to the profile.

   Queuing       A combination of functional datapath elements
   Block         that modulates the transmission of packets belonging
                 to a traffic streams and determines their
                 ordering, possibly storing them temporarily or
                 discarding them.

   Scheduling    An algorithm which determines which queue of a set
   algorithm     of queues to service next.  This may be based on the
                 relative priority of the queues, on a weighted fair
                 bandwidth sharing policy or some other policy. Such
                 an algorithm may be either work-conserving or non-
                 work-conserving.

   Service-Level A set of parameters and their values which together
   Specification define the treatment offered to a traffic stream by a
   (SLS)         Diffserv domain.

   Shaping       The process of delaying packets within a traffic stream
                 to cause it to conform to some defined temporal
                 profile.  Shaping can be implemented using a queue
                 serviced by a non-work-conserving scheduling algorithm.

   Traffic       A logical datapath entity consisting of a number of
   Conditioning  functional datapath elements interconnected in
   Block (TCB)   such a way as to perform a specific set of traffic
                 conditioning functions on an incoming traffic stream.
                 A TCB can be thought of as an entity with one
                 input and one or more outputs and a set of control
                 parameters.

   Traffic       A set of parameters and their values which together
   Conditioning  specify a set of classifier rules and a traffic
   Specification profile.  A TCS is an integral element of a SLS.
   (TCS)






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   Work-         A property of a scheduling algorithm such that it
   conserving    services a packet, if one is available, at every
                 transmission opportunity.

3.  Conceptual Model

   This section introduces a block diagram of a Diffserv router and
   describes the various components illustrated in Figure 1.  Note that
   a Diffserv core router is likely to require only a subset of these
   components: the model presented here is intended to cover the case of
   both Diffserv edge and core routers.

3.1.  Components of a Diffserv Router

   The conceptual model includes abstract definitions for the following:

      o  Traffic Classification elements.

      o  Metering functions.

      o  Actions of Marking, Absolute Dropping, Counting, and
         Multiplexing.

      o  Queuing elements, including capabilities of algorithmic
         dropping and scheduling.

      o  Certain combinations of the above functional datapath elements
         into higher-level blocks known as Traffic Conditioning Blocks
         (TCBs).

   The components and combinations of components described in this
   document form building blocks that need to be manageable by Diffserv
   configuration and management tools.  One of the goals of this
   document is to show how a model of a Diffserv device can be built
   using these component blocks.  This model is in the form of a
   connected directed acyclic graph (DAG) of functional datapath
   elements that describes the traffic conditioning and queuing
   behaviors that any particular packet will experience when forwarded
   to the Diffserv router.  Figure 1 illustrates the major functional
   blocks of a Diffserv router.

3.1.1.  Datapath

   An ingress interface, routing core, and egress interface are
   illustrated at the center of the diagram.  In actual router
   implementations, there may be an arbitrary number of ingress and
   egress interfaces interconnected by the routing core.  The routing
   core element serves as an abstraction of a router's normal routing



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   and switching functionality.  The routing core moves packets between
   interfaces according to policies outside the scope of Diffserv (note:
   it is possible that such policies for output-interface selection
   might involve use of packet fields such as the DSCP but this is
   outside the scope of this model).  The actual queuing delay and
   packet loss behavior of a specific router's switching
   fabric/backplane is not modeled by the routing core; these should be
   modeled using the functional datapath elements described later.  The
   routing core of this model can be thought of as an infinite
   bandwidth, zero-delay interconnect between interfaces - properties
   like the behavior of the core when overloaded need to be reflected
   back into the queuing elements that are modeled around it (e.g., when
   too much traffic is directed across the core at an egress interface),
   the excess must either be dropped or queued somewhere: the elements
   performing these functions must be modeled on one of the interfaces
   involved.

   The components of interest at the ingress to and egress from
   interfaces are the functional datapath elements (e.g., Classifiers,
   Queuing elements) that support Diffserv traffic conditioning and
   per-hop behaviors [DSARCH].  These are the fundamental components
   comprising a Diffserv router and are the focal point of this model.





























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               +---------------+
               | Diffserv      |
        Mgmt   | configuration |
      <----+-->| & management  |------------------+
      SNMP,|   | interface     |                  |
      COPS |   +---------------+                  |
      etc. |        |                             |
           |        |                             |
           |        v                             v
           |   +-------------+                 +-------------+
           |   | ingress i/f |   +---------+   | egress i/f  |
      -------->|  classify,  |-->| routing |-->|  classify,  |---->
      data |   |  meter,     |   |  core   |   |  meter      |data out
      in   |   |  action,    |   +---------+   |  action,    |
           |   |  queuing    |                 |  queuing    |
           |   +-------------+                 +-------------+
           |        ^                             ^
           |        |                             |
           |        |                             |
           |   +------------+                     |
           +-->| QOS agent  |                     |
      -------->| (optional) |---------------------+
        QOS    |(e.g., RSVP)|
        cntl   +------------+
        msgs

           Figure 1:  Diffserv Router Major Functional Blocks

3.1.2.  Configuration and Management Interface

   Diffserv operating parameters are monitored and provisioned through
   this interface.  Monitored parameters include statistics regarding
   traffic carried at various Diffserv service levels.  These statistics
   may be important for accounting purposes and/or for tracking
   compliance to Traffic Conditioning Specifications (TCSs) negotiated
   with customers.  Provisioned parameters are primarily the TCS
   parameters for Classifiers and Meters and the associated PHB
   configuration parameters for Actions and Queuing elements.  The
   network administrator interacts with the Diffserv configuration and
   management interface via one or more management protocols, such as
   SNMP or COPS, or through other router configuration tools such as
   serial terminal or telnet consoles.

   Specific policy rules and goals governing the Diffserv behavior of a
   router are presumed to be installed by policy management mechanisms.
   However, Diffserv routers are always subject to implementation limits





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   which scope the kinds of policies which can be successfully
   implemented by the router.  External reporting of such implementation
   capabilities is considered out of scope for this document.

3.1.3.  Optional QoS Agent Module

   Diffserv routers may snoop or participate in either per-microflow or
   per-flow-aggregate signaling of QoS requirements [E2E] (e.g., using
   the RSVP protocol).  Snooping of RSVP messages may be used, for
   example, to learn how to classify traffic without actually
   participating as a RSVP protocol peer.  Diffserv routers may reject
   or admit RSVP reservation requests to provide a means of admission
   control to Diffserv-based services or they may use these requests to
   trigger provisioning changes for a flow-aggregation in the Diffserv
   network.  A flow-aggregation in this context might be equivalent to a
   Diffserv BA or it may be more fine-grained, relying on a multi-field
   (MF) classifier [DSARCH].  Note that the conceptual model of such a
   router implements the Integrated Services Model as described in
   [INTSERV], applying the control plane controls to the data classified
   and conditioned in the data plane, as described in [E2E].

   Note that a QoS Agent component of a Diffserv router, if present,
   might be active only in the control plane and not in the data plane.
   In this scenario, RSVP could be used merely to signal reservation
   state without installing any actual reservations in the data plane of
   the Diffserv router: the data plane could still act purely on
   Diffserv DSCPs and provide PHBs for handling data traffic without the
   normal per-microflow handling expected to support some Intserv
   services.

3.2.  Diffserv Functions at Ingress and Egress

   This document focuses on the Diffserv-specific components of the
   router.  Figure 2 shows a high-level view of ingress and egress
   interfaces of a router.  The diagram illustrates two Diffserv router
   interfaces, each having a set of ingress and a set of egress
   elements.  It shows classification, metering, action and queuing
   functions which might be instantiated at each interface's ingress and
   egress.

   The simple diagram of Figure 2 assumes that the set of Diffserv
   functions to be carried out on traffic on a given interface are
   independent of those functions on all other interfaces.  There are
   some architectures where Diffserv functions may be shared amongst
   multiple interfaces (e.g., processor and buffering resources that
   handle multiple interfaces on the same line card before forwarding
   across a routing core).  The model presented in this document may be
   easily extended to handle such cases; however, this topic is not



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   treated further here as it leads to excessive complexity in the
   explanation of the concepts.

            Interface A                        Interface B
          +-------------+     +---------+     +-------------+
          | ingress:    |     |         |     | egress:     |
          |   classify, |     |         |     |   classify, |
      --->|   meter,    |---->|         |---->|   meter,    |--->
          |   action,   |     |         |     |   action,   |
          |   queuing   |     | routing |     |   queuing   |
          +-------------+     |  core   |     +-------------+
          | egress:     |     |         |     | ingress:    |
          |   classify, |     |         |     |   classify, |
      <---|   meter,    |<----|         |<----|   meter,    |<---
          |   action,   |     |         |     |   action,   |
          |   queuing   |     +---------+     |   queuing   |
          +-------------+                     +-------------+

          Figure 2. Traffic Conditioning and Queuing Elements

   In principle, if one were to construct a network entirely out of
   two-port routers (connected by LANs or similar media), then it might
   be necessary for each router to perform four QoS control functions in
   the datapath on traffic in each direction:

   -  Classify each message according to some set of rules, possibly
      just a "match everything" rule.

   -  If necessary, determine whether the data stream the message is
      part of is within or outside its rate by metering the stream.

   -  Perform a set of resulting actions, including applying a drop
      policy appropriate to the classification and queue in question and
      perhaps additionally marking the traffic with a Differentiated
      Services Code Point (DSCP) [DSFIELD].

   -  Enqueue the traffic for output in the appropriate queue.  The
      scheduling of output from this queue may lead to shaping of the
      traffic or may simply cause it to be forwarded with some minimum
      rate or maximum latency assurance.

   If the network is now built out of N-port routers, the expected
   behavior of the network should be identical.  Therefore, this model
   must provide for essentially the same set of functions at the ingress
   as on the egress of a router's interfaces.  The one point of
   difference in the model between ingress and the egress is that all
   traffic at the egress of an interface is queued, while traffic at the
   ingress to an interface is likely to be queued only for shaping



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   purposes, if at all.  Therefore, equivalent functional datapath
   elements may be modeled at both the ingress to and egress from an
   interface.

   Note that it is not mandatory that each of these functional datapath
   elements be implemented at both ingress and egress; equally, the
   model allows that multiple sets of these elements may be placed in
   series and/or in parallel at ingress or at egress.  The arrangement
   of elements is dependent on the service requirements on a particular
   interface on a particular router.  By modeling these elements at both
   ingress and egress, it is not implied that they must be implemented
   in this way in a specific router.  For example, a router may
   implement all shaping and PHB queuing at the interface egress or may
   instead implement it only at the ingress.  Furthermore, the
   classification needed to map a packet to an egress queue (if present)
   need not be implemented at the egress but instead might be
   implemented at the ingress, with the packet passed through the
   routing core with in-band control information to allow for egress
   queue selection.

   Specifically, some interfaces will be at the outer "edge" and some
   will be towards the "core" of the Diffserv domain.  It is to be
   expected (from the general principles guiding the motivation of
   Diffserv) that "edge" interfaces, or at least the routers that
   contain them, will implement more complexity and require more
   configuration than those in the core although this is obviously not a
   requirement.

3.3.  Shaping and Policing

   Diffserv nodes may apply shaping, policing and/or marking to traffic
   streams that exceed the bounds of their TCS in order to prevent one
   traffic stream from seizing more than its share of resources from a
   Diffserv network.  In this model, Shaping, sometimes considered as a
   TC action, is treated as a function of queuing elements - see section
   7.  Algorithmic Dropping techniques (e.g., RED) are similarly treated
   since they are often closely associated with queues.  Policing is
   modeled as either a concatenation of a Meter with an Absolute Dropper
   or as a concatenation of an Algorithmic Dropper with a Scheduler.
   These elements will discard packets which exceed the TCS.

3.4.  Hierarchical View of the Model

   From a device-level configuration management perspective, the
   following hierarchy exists:






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      At the lowest level considered here, there are individual
      functional datapath elements, each with their own configuration
      parameters and management counters and flags.

      At the next level, the network administrator manages groupings of
      these functional datapath elements interconnected in a DAG.  These
      functional datapath elements are organized in self-contained TCBs
      which are used to implement some desired network policy (see
      Section 8).  One or more TCBs may be instantiated at each
      interface's ingress or egress; they may be connected in series
      and/or in parallel configurations on the multiple outputs of a
      preceding TCB.  A TCB can be thought of as a "black box" with one
      input and one or more outputs (in the data path).  Each interface
      may have a different TCB configuration and each direction (ingress
      or egress) may too.

      At the topmost level considered here, the network administrator
      manages interfaces.  Each interface has ingress and egress
      functionality, with each of these expressed as one or more TCBs.
      This level of the hierarchy is what was illustrated in Figure 2.

   Further levels may be built on top of this hierarchy, in particular
   ones for aiding in the repetitive configuration tasks likely for
   routers with many interfaces: some such "template" tools for Diffserv
   routers are outside the scope of this model but are under study by
   other working groups within IETF.

4.  Classifiers

4.1.  Definition

   Classification is performed by a classifier element.  Classifiers are
   1:N (fan-out) devices: they take a single traffic stream as input and
   generate N logically separate traffic streams as output.  Classifiers
   are parameterized by filters and output streams.  Packets from the
   input stream are sorted into various output streams by filters which
   match the contents of the packet or possibly match other attributes
   associated with the packet.  Various types of classifiers using
   different filters are described in the following sections.  Figure 3
   illustrates a classifier, where the outputs connect to succeeding
   functional datapath elements.

   The simplest possible Classifier element is one that matches all
   packets that are applied at its input.  In this case, the Classifier
   element is just a no-op and may be omitted.






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   Note that we allow a Multiplexor (see Section 6.5) before the
   Classifier to allow input from multiple traffic streams.  For
   example, if traffic streams originating from multiple ingress
   interfaces feed through a single Classifier then the interface number
   could be one of the packet classification keys used by the
   Classifier.  This optimization may be important for scalability in
   the management plane.  Classifiers may also be cascaded in sequence
   to perform more complex lookup operations whilst still maintaining
   such scalability.

   Another example of a packet attribute could be an integer
   representing the BGP community string associated with the packet's
   best-matching route.  Other contextual information may also be used
   by a Classifier (e.g., knowledge that a particular interface faces a
   Diffserv domain or a legacy IP TOS domain [DSARCH] could be used when
   determining whether a DSCP is present or not).

      unclassified              classified
      traffic                   traffic
              +------------+
              |            |--> match Filter1 --> OutputA
      ------->| classifier |--> match Filter2 --> OutputB
              |            |--> no match      --> OutputC
              +------------+

      Figure 3. An Example Classifier

   The following BA classifier separates traffic into one of three
   output streams based on matching filters:

      Filter Matched        Output Stream
      --------------       ---------------
      Filter1                    A
      Filter2                    B
      no match                   C

   Where the filters are defined to be the following BA filters
   ([DSARCH], Section 4.2.1):

      Filter        DSCP
      ------       ------
      Filter1       101010
      Filter2       111111
      Filter3       ****** (wildcard)







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4.1.1.  Filters

   A filter consists of a set of conditions on the component values of a
   packet's classification key (the header values, contents, and
   attributes relevant for classification).  In the BA classifier
   example above, the classification key consists of one packet header
   field, the DSCP, and both Filter1 and Filter2 specify exact-match
   conditions on the value of the DSCP.  Filter3 is a wildcard default
   filter which matches every packet, but which is only selected in the
   event that no other more specific filter matches.

   In general there are a set of possible component conditions including
   exact, prefix, range, masked and wildcard matches.  Note that ranges
   can be represented (with less efficiency) as a set of prefixes and
   that prefix matches are just a special case of both masked and range
   matches.

   In the case of a MF classifier, the classification key consists of a
   number of packet header fields.  The filter may specify a different
   condition for each key component, as illustrated in the example below
   for a IPv4/TCP classifier:

      Filter   IPv4 Src Addr  IPv4 Dest Addr  TCP SrcPort  TCP DestPort
      ------   -------------  --------------  -----------  ------------
      Filter4  172.31.8.1/32  172.31.3.X/24       X          5003

   In this example, the fourth octet of the destination IPv4 address and
   the source TCP port are wildcard or "don't care".

   MF classification of IP-fragmented packets is impossible if the
   filter uses transport-layer port numbers (e.g., TCP port numbers).
   MTU-discovery is therefore a prerequisite for proper operation of a
   Diffserv network that uses such classifiers.

4.1.2.  Overlapping Filters

   Note that it is easy to define sets of overlapping filters in a
   classifier.  For example:

      Filter   IPv4 Src Addr  IPv4 Dest Addr
      ------   -------------  --------------
      Filter5  172.31.8.X/24      X/0
      Filter6      X/0        172.30.10.1/32

   A packet containing {IP Dest Addr 172.31.8.1, IP Src Addr
   172.30.10.1} cannot be uniquely classified by this pair of filters
   and so a precedence must be established between Filter5 and Filter6
   in order to break the tie.  This precedence must be established



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   either (a) by a manager which knows that the router can accomplish
   this particular ordering (e.g., by means of reported capabilities),
   or (b) by the router along with a mechanism to report to a manager
   which precedence is being used.  Such precedence mechanisms must be
   supported in any translation of this model into specific syntax for
   configuration and management protocols.

   As another example, one might want first to disallow certain
   applications from using the network at all, or to classify some
   individual traffic streams that are not Diffserv-marked.  Traffic
   that is not classified by those tests might then be inspected for a
   DSCP.  The word "then" implies sequence and this must be specified by
   means of precedence.

   An unambiguous classifier requires that every possible classification
   key match at least one filter (possibly the wildcard default) and
   that any ambiguity between overlapping filters be resolved by
   precedence.  Therefore, the classifiers on any given interface must
   be "complete" and will often include an "everything else" filter as
   the lowest precedence element in order for the result of
   classification to be deterministic.  Note that this completeness is
   only required of the first classifier that incoming traffic will meet
   as it enters an interface - subsequent classifiers on an interface
   only need to handle the traffic that it is known that they will
   receive.

   This model of classifier operation makes the assumption that all
   filters of the same precedence be applied simultaneously.  Whilst
   convenient from a modeling point-of-view, this may or may not be how
   the classifier is actually implemented - this assumption is not
   intended to dictate how the implementation actually handles this,
   merely to clearly define the required end result.

4.2.  Examples

4.2.1.  Behavior Aggregate (BA) Classifier

   The simplest Diffserv classifier is a behavior aggregate (BA)
   classifier [DSARCH].  A BA classifier uses only the Diffserv
   codepoint (DSCP) in a packet's IP header to determine the logical
   output stream to which the packet should be directed.  We allow only
   an exact-match condition on this field because the assigned DSCP
   values have no structure, and therefore no subset of DSCP bits are
   significant.







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   The following defines a possible BA filter:

      Filter8:
      Type:   BA
      Value:  111000

4.2.2.  Multi-Field (MF) Classifier

   Another type of classifier is a multi-field (MF) classifier [DSARCH].
   This classifies packets based on one or more fields in the packet
   (possibly including the DSCP).  A common type of MF classifier is a
   6-tuple classifier that classifies based on six fields from the IP
   and TCP or UDP headers (destination address, source address, IP
   protocol, source port, destination port, and DSCP).  MF classifiers
   may classify on other fields such as MAC addresses, VLAN tags, link-
   layer traffic class fields, or other higher-layer protocol fields.

   The following defines a possible MF filter:

      Filter9:
      Type:              IPv4-6-tuple
      IPv4DestAddrValue: 0.0.0.0
      IPv4DestAddrMask:  0.0.0.0
      IPv4SrcAddrValue:  172.31.8.0
      IPv4SrcAddrMask:   255.255.255.0
      IPv4DSCP:          28
      IPv4Protocol:      6
      IPv4DestL4PortMin: 0
      IPv4DestL4PortMax: 65535
      IPv4SrcL4PortMin:  20
      IPv4SrcL4PortMax:  20

   A similar type of classifier can be defined for IPv6.

4.2.3.  Free-form Classifier

   A Free-form classifier is made up of a set of user definable
   arbitrary filters each made up of {bit-field size, offset (from head
   of packet), mask}:

      Classifier2:
      Filter12:    OutputA
      Filter13:    OutputB
      Default:     OutputC







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      Filter12:
      Type:        FreeForm
      SizeBits:    3 (bits)
      Offset:      16 (bytes)
      Value:       100 (binary)
      Mask:        101 (binary)

      Filter13:
      Type:        FreeForm
      SizeBits:    12 (bits)
      Offset:      16 (bytes)
      Value:       100100000000 (binary)
      Mask:        111111111111 (binary)

   Free-form filters can be combined into filter groups to form very
   powerful filters.

4.2.4.  Other Possible Classifiers

   Classification may also be performed based on information at the
   datalink layer below IP (e.g., VLAN or datalink-layer priority) or
   perhaps on the ingress or egress IP, logical or physical interface
   identifier (e.g., the incoming channel number on a channelized
   interface).  A classifier that filters based on IEEE 802.1p Priority
   and on 802.1Q VLAN-ID might be represented as:

      Classifier3:
      Filter14 AND Filter15:  OutputA
      Default:                OutputB

      Filter14:                        -- priority 4 or 5
      Type:        Ieee8021pPriority
      Value:       100 (binary)
      Mask:        110 (binary)

      Filter15:                        -- VLAN 2304
      Type:        Ieee8021QVlan
      Value:       100100000000 (binary)
      Mask:        111111111111 (binary)

   Such classifiers may be the subject of other standards or may be
   proprietary to a router vendor but they are not discussed further
   here.








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5.  Meters

   Metering is defined in [DSARCH].  Diffserv network providers may
   choose to offer services to customers based on a temporal (i.e.,
   rate) profile within which the customer submits traffic for the
   service.  In this event, a meter might be used to trigger real-time
   traffic conditioning actions (e.g., marking) by routing a non-
   conforming packet through an appropriate next-stage action element.
   Alternatively, by counting conforming and/or non-conforming traffic
   using a Counter element downstream of the Meter, it might also be
   used to help in collecting data for out-of-band management functions
   such as billing applications.

   Meters are logically 1:N (fan-out) devices (although a multiplexor
   can be used in front of a meter).  Meters are parameterized by a
   temporal profile and by conformance levels, each of which is
   associated with a meter's output.  Each output can be connected to
   another functional element.

   Note that this model of a meter differs slightly from that described
   in [DSARCH].  In that description the meter is not a datapath element
   but is instead used to monitor the traffic stream and send control
   signals to action elements to dynamically modulate their behavior
   based on the conformance of the packet.  This difference in the
   description does not change the function of a meter.  Figure 4
   illustrates a meter with 3 levels of conformance.

   In some Diffserv examples (e.g., [AF-PHB]), three levels of
   conformance are discussed in terms of colors, with green representing
   conforming, yellow representing partially conforming and red
   representing non-conforming.  These different conformance levels may
   be used to trigger different queuing, marking or dropping treatment
   later on in the processing.  Other example meters use a binary notion
   of conformance; in the general case N levels of conformance can be
   supported.  In general there is no constraint on the type of
   functional datapath element following a meter output, but care must
   be taken not to inadvertently configure a datapath that results in
   packet reordering that is not consistent with the requirements of the
   relevant PHB specification.












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      unmetered              metered
      traffic                traffic
                +---------+
                |         |--------> conformance A
      --------->|  meter  |--------> conformance B
                |         |--------> conformance C
                +---------+

      Figure 4. A Generic Meter

   A meter, according to this model, measures the rate at which packets
   making up a stream of traffic pass it, compares the rate to some set
   of thresholds, and produces some number of potential results (two or
   more):  a given packet is said to be "conformant" to a level of the
   meter if, at the time that the packet is being examined, the stream
   appears to be within the rate limit for the profile associated with
   that level.  A fuller discussion of conformance to meter profiles
   (and the associated requirements that this places on the schedulers
   upstream) is provided in Appendix A.

5.1.  Examples

   The following are some examples of possible meters.

5.1.1.  Average Rate Meter

   An example of a very simple meter is an average rate meter.  This
   type of meter measures the average rate at which packets are
   submitted to it over a specified averaging time.

   An average rate profile may take the following form:

      Meter1:
      Type:                AverageRate
      Profile:             Profile1
      ConformingOutput:    Queue1
      NonConformingOutput: Counter1

      Profile1:
      Type:                AverageRate
      AverageRate:         120 kbps
      Delta:               100 msec

   A Meter measuring against this profile would continually maintain a
   count that indicates the total number and/or cumulative byte-count of
   packets arriving between time T (now) and time T - 100 msecs.  So
   long as an arriving packet does not push the count over 12 kbits in
   the last 100 msec, the packet would be deemed conforming.  Any packet



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   that pushes the count over 12 kbits would be deemed non-conforming.
   Thus, this Meter deems packets to correspond to one of two
   conformance levels: conforming or non-conforming, and sends them on
   for the appropriate subsequent treatment.

5.1.2.  Exponential Weighted Moving Average (EWMA) Meter

   The EWMA form of Meter is easy to implement in hardware and can be
   parameterized as follows:

      avg_rate(t) = (1 - Gain) * avg_rate(t') +  Gain * rate(t)
      t = t' + Delta

   For a packet arriving at time t:

      if (avg_rate(t) > AverageRate)
         non-conforming
      else
         conforming

   "Gain" controls the time constant (e.g., frequency response) of what
   is essentially a simple IIR low-pass filter.  "Rate(t)" measures the
   number of incoming bytes in a small fixed sampling interval, Delta.
   Any packet that arrives and pushes the average rate over a predefined
   rate AverageRate is deemed non-conforming.  An EWMA Meter profile
   might look something like the following:

      Meter2:
      Type:                ExpWeightedMovingAvg
      Profile:             Profile2
      ConformingOutput:    Queue1
      NonConformingOutput: AbsoluteDropper1

      Profile2:
      Type:                ExpWeightedMovingAvg
      AverageRate:         25 kbps
      Delta:               10 usec
      Gain:                1/16

5.1.3.  Two-Parameter Token Bucket Meter

   A more sophisticated Meter might measure conformance to a token
   bucket (TB) profile.  A TB profile generally has two parameters, an
   average token rate, R, and a burst size, B.  TB Meters compare the
   arrival rate of packets to the average rate specified by the TB
   profile.  Logically, tokens accumulate in a bucket at the average





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   rate, R, up to a maximum credit which is the burst size, B.  When a
   packet of length L arrives, a conformance test is applied.  There are
   at least two such tests in widespread use:

   Strict conformance
      Packets of length L bytes are considered conforming only if there
      are sufficient tokens available in the bucket at the time of
      packet arrival for the complete packet (i.e., the current depth is
      greater than or equal to L): no tokens may be borrowed from future
      token allocations.  For examples of this approach, see [SRTCM] and
      [TRTCM].

   Loose conformance
      Packets of length L bytes are considered conforming if any tokens
      are available in the bucket at the time of packet arrival: up to L
      bytes may then be borrowed from future token allocations.

   Packets are allowed to exceed the average rate in bursts up to the
   burst size.  For further discussion of loose and strict conformance
   to token bucket profiles, as well as system and implementation
   issues, see Appendix A.

   A two-parameter TB meter has exactly two possible conformance levels
   (conforming, non-conforming).  Such a meter might appear as follows:

      Meter3:
      Type:                SimpleTokenBucket
      Profile:             Profile3
      ConformanceType:     loose
      ConformingOutput:    Queue1
      NonConformingOutput: AbsoluteDropper1

      Profile3:
      Type:                SimpleTokenBucket
      AverageRate:         200 kbps
      BurstSize:           100 kbytes

5.1.4.  Multi-Stage Token Bucket Meter

   More complicated TB meters might define multiple burst sizes and more
   conformance levels.  Packets found to exceed the larger burst size
   are deemed non-conforming.  Packets found to exceed the smaller burst
   size are deemed partially-conforming.  Packets exceeding neither are
   deemed conforming.  Some token bucket meters designed for Diffserv
   networks are described in more detail in [SRTCM, TRTCM]; in some of
   these references, three levels of conformance are discussed in terms
   of colors with green representing conforming, yellow representing
   partially conforming, and red representing non-conforming.  Note that



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   these multiple-conformance-level meters can sometimes be implemented
   using an appropriate sequence of multiple two-parameter TB meters.

   A profile for a multi-stage TB meter with three levels of conformance
   might look as follows:

      Meter4:
      Type:                TwoRateTokenBucket
      ProfileA:            Profile4
      ConformanceTypeA:    strict
      ConformingOutputA:   Queue1

      ProfileB:            Profile5
      ConformanceTypeB:    strict
      ConformingOutputB:   Marker1
      NonConformingOutput: AbsoluteDropper1

      Profile4:
      Type:                SimpleTokenBucket
      AverageRate:         100 kbps
      BurstSize:           20 kbytes

      Profile5:
      Type:                SimpleTokenBucket
      AverageRate:         100 kbps
      BurstSize:           100 kbytes

5.1.5.  Null Meter

   A null meter has only one output: always conforming, and no
   associated temporal profile.  Such a meter is useful to define in the
   event that the configuration or management interface does not have
   the flexibility to omit a meter in a datapath segment.

      Meter5:
      Type:                NullMeter
      Output:              Queue1

6.  Action Elements

   The classifiers and meters described up to this point are fan-out
   elements which are generally used to determine the appropriate action
   to apply to a packet.  The set of possible actions that can then be
   applied include:

   -    Marking

   -    Absolute Dropping



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   -    Multiplexing

   -    Counting

   -    Null action - do nothing

   The corresponding action elements are described in the following
   sections.

6.1.  DSCP Marker

   DSCP Markers are 1:1 elements which set a codepoint (e.g., the DSCP
   in an IP header).  DSCP Markers may also act on unmarked packets
   (e.g., those submitted with DSCP of zero) or may re-mark previously
   marked packets.  In particular, the model supports the application of
   marking based on a preceding classifier match.  The mark set in a
   packet will determine its subsequent PHB treatment in downstream
   nodes of a network and possibly also in subsequent processing stages
   within this router.

   DSCP Markers for Diffserv are normally parameterized by a single
   parameter: the 6-bit DSCP to be marked in the packet header.

      Marker1:
      Type:                DSCPMarker
      Mark:                010010

6.2.  Absolute Dropper

   Absolute Droppers simply discard packets.  There are no parameters
   for these droppers.  Because this Absolute Dropper is a terminating
   point of the datapath and has no outputs, it is probably desirable to
   forward the packet through a Counter Action first for instrumentation
   purposes.

      AbsoluteDropper1:
      Type:                AbsoluteDropper

   Absolute Droppers are not the only elements than can cause a packet
   to be discarded: another element is an Algorithmic Dropper element
   (see Section 7.1.3).  However, since this element's behavior is
   closely tied the state of one or more queues, we choose to
   distinguish it as a separate functional datapath element.








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6.3.  Multiplexor

   It is occasionally necessary to multiplex traffic streams into a
   functional datapath element with a single input.  A M:1 (fan-in)
   multiplexor is a simple logical device for merging traffic streams.
   It is parameterized by its number of incoming ports.

      Mux1:
      Type:                Multiplexor
      Output:              Queue2

6.4.  Counter

   One passive action is to account for the fact that a data packet was
   processed.  The statistics that result might be used later for
   customer billing, service verification or network engineering
   purposes.  Counters are 1:1 functional datapath elements which update
   a counter by L and a packet counter by 1 every time a L-byte sized
   packet passes through them.  Counters can be used to count packets
   about to be dropped by an Absolute Dropper or to count packets
   arriving at or departing from some other functional element.

      Counter1:
      Type:                Counter
      Output:              Queue1

6.5.  Null Action

   A null action has one input and one output.  The element performs no
   action on the packet.  Such an element is useful to define in the
   event that the configuration or management interface does not have
   the flexibility to omit an action element in a datapath segment.

      Null1:
      Type:                Null
      Output:              Queue1

7.  Queuing Elements

   Queuing elements modulate the transmission of packets belonging to
   the different traffic streams and determine their ordering, possibly
   storing them temporarily or discarding them.  Packets are usually
   stored either because there is a resource constraint (e.g., available
   bandwidth) which prevents immediate forwarding, or because the
   queuing block is being used to alter the temporal properties of a
   traffic stream (i.e., shaping).  Packets are discarded for one of the
   following reasons:




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      -  because of buffering limitations.
      -  because a buffer threshold is exceeded (including when shaping
         is performed).
      -  as a feedback control signal to reactive control protocols such
         as TCP.
      -  because a meter exceeds a configured profile (i.e., policing).

   The queuing elements in this model represent a logical abstraction of
   a queuing system which is used to configure PHB-related parameters.
   The model can be used to represent a broad variety of possible
   implementations.  However, it need not necessarily map one-to-one
   with physical queuing systems in a specific router implementation.
   Implementors should map the configurable parameters of the
   implementation's queuing systems to these queuing element parameters
   as appropriate to achieve equivalent behaviors.

7.1.  Queuing Model

   Queuing is a function which lends itself to innovation.  It must be
   modeled to allow a broad range of possible implementations to be
   represented using common structures and parameters.  This model uses
   functional decomposition as a tool to permit the needed latitude.

   Queuing systems perform three distinct, but related, functions:  they
   store packets, they modulate the departure of packets belonging to
   various traffic streams and they selectively discard packets.  This
   model decomposes queuing into the component elements that perform
   each of these functions: Queues, Schedulers, and Algorithmic
   Droppers, respectively.  These elements may be connected together as
   part of a TCB, as described in section 8.

   The remainder of this section discusses FIFO Queues: typically, the
   Queue element of this model will be implemented as a FIFO data
   structure.  However, this does not preclude implementations which are
   not strictly FIFO, in that they also support operations that remove
   or examine packets (e.g., for use by discarders) other than at the
   head or tail.  However, such operations must not have the effect of
   reordering packets belonging to the same microflow.

   Note that the term FIFO has multiple different common usages: it is
   sometimes taken to mean, among other things, a data structure that
   permits items to be removed only in the order in which they were
   inserted or a service discipline which is non-reordering.








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7.1.1.  FIFO Queue

   In this model, a FIFO Queue element is a data structure which at any
   time may contain zero or more packets.  It may have one or more
   thresholds associated with it.  A FIFO has one or more inputs and
   exactly one output.  It must support an enqueue operation to add a
   packet to the tail of the queue and a dequeue operation to remove a
   packet from the head of the queue.  Packets must be dequeued in the
   order in which they were enqueued.  A FIFO has a current depth, which
   indicates the number of packets and/or bytes that it contains at a
   particular time.  FIFOs in this model are modeled without inherent
   limits on their depth - obviously this does not reflect the reality
   of implementations: FIFO size limits are modeled here by an
   algorithmic dropper associated with the FIFO, typically at its input.
   It is quite likely that every FIFO will be preceded by an algorithmic
   dropper.  One exception might be the case where the packet stream has
   already been policed to a profile that can never exceed the scheduler
   bandwidth available at the FIFO's output - this would not need an
   algorithmic dropper at the input to the FIFO.

   This representation of a FIFO allows for one common type of depth
   limit, one that results from a FIFO supplied from a limited pool of
   buffers, shared between multiple FIFOs.

   In an implementation, packets are presumably stored in one or more
   buffers.  Buffers are allocated from one or more free buffer pools.
   If there are multiple instances of a FIFO, their packet buffers may
   or may not be allocated out of the same free buffer pool.  Free
   buffer pools may also have one or more thresholds associated with
   them, which may affect discarding and/or scheduling.  Other than
   this, buffering mechanisms are implementation specific and not part
   of this model.

   A FIFO might be represented using the following parameters:

      Queue1:
      Type:       FIFO
      Output:     Scheduler1

   Note that a FIFO must provide triggers and/or current state
   information to other elements upstream and downstream from it: in
   particular, it is likely that the current depth will need to be used
   by Algorithmic Dropper elements placed before or after the FIFO.  It
   will also likely need to provide an implicit "I have packets for you"
   signal to downstream Scheduler elements.






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7.1.2.  Scheduler

   A scheduler is an element which gates the departure of each packet
   that arrives at one of its inputs, based on a service discipline.  It
   has one or more inputs and exactly one output.  Each input has an
   upstream element to which it is connected, and a set of parameters
   that affects the scheduling of packets received at that input.

   The service discipline (also known as a scheduling algorithm) is an
   algorithm which might take any of the following as its input(s):

   a) static parameters such as relative priority associated with each
      of the scheduler's inputs.

   b) absolute token bucket parameters for maximum or minimum rates
      associated with each of the scheduler's inputs.

   c) parameters, such as packet length or DSCP, associated with the
      packet currently present at its input.

   d) absolute time and/or local state.

   Possible service disciplines fall into a number of categories,
   including (but not limited to) first come, first served (FCFS),
   strict priority, weighted fair bandwidth sharing (e.g., WFQ), rate-
   limited strict priority, and rate-based.  Service disciplines can be
   further distinguished by whether they are work-conserving or non-
   work-conserving (see Glossary).  Non-work-conserving schedulers can
   be used to shape traffic streams to match some profile by delaying
   packets that might be deemed non-conforming by some downstream node:
   a packet is delayed until such time as it would conform to a
   downstream meter using the same profile.

   [DSARCH] defines PHBs without specifying required scheduling
   algorithms.  However, PHBs such as the class selectors [DSFIELD], EF
   [EF-PHB] and AF [AF-PHB] have descriptions or configuration
   parameters which strongly suggest the sort of scheduling discipline
   needed to implement them.  This document discusses a minimal set of
   queue parameters to enable realization of these PHBs.  It does not
   attempt to specify an all-embracing set of parameters to cover all
   possible implementation models.  A minimal set includes:

   a) a minimum service rate profile which allows rate guarantees for
      each traffic stream as required by EF and AF without specifying
      the details of how excess bandwidth between these traffic streams
      is shared.  Additional parameters to control this behavior should
      be made available, but are dependent on the particular scheduling
      algorithm implemented.



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   b) a service priority, used only after the minimum rate profiles of
      all inputs have been satisfied, to decide how to allocate any
      remaining bandwidth.

   c) a maximum service rate profile, for use only with a non-work-
      conserving service discipline.

   Any one of these profiles is composed, for the purposes of this
   model, of both a rate (in suitable units of bits, bytes or larger
   chunks in some unit of time) and a burst size, as discussed further
   in Appendix A.

   By way of example, for an implementation of the EF PHB using a strict
   priority scheduling algorithm that assumes that the aggregate EF rate
   has been appropriately bounded by upstream policing to avoid
   starvation of other BAs, the service rate profiles are not used: the
   minimum service rate profile would be defaulted to zero and the
   maximum service rate profile would effectively be the "line rate".
   Such an implementation, with multiple priority classes, could also be
   used for the Diffserv class selectors [DSFIELD].

   Alternatively, setting the service priority values for each input to
   the scheduler to the same value enables the scheduler to satisfy the
   minimum service rates for each input, so long as the sum of all
   minimum service rates is less than or equal to the line rate.

   For example, a non-work-conserving scheduler, allocating spare
   bandwidth equally between all its inputs, might be represented using
   the following parameters:

      Scheduler1:
      Type:           Scheduler2Input

      Input1:
      MaxRateProfile: Profile1
      MinRateProfile: Profile2
      Priority:       none

      Input2:
      MaxRateProfile: Profile3
      MinRateProfile: Profile4
      Priority:       none

   A work-conserving scheduler might be represented using the following
   parameters:






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      Scheduler2:
      Type:           Scheduler3Input
      Input1:
      MaxRateProfile: WorkConserving
      MinRateProfile: Profile5
      Priority:       1

      Input2:
      MaxRateProfile: WorkConserving
      MinRateProfile: Profile6
      Priority:       2

      Input3:
      MaxRateProfile: WorkConserving
      MinRateProfile: none
      Priority:       3

7.1.3.  Algorithmic Dropper

   An Algorithmic Dropper is an element which selectively discards
   packets that arrive at its input, based on a discarding algorithm.
   It has one data input and one output.  In this model (but not
   necessarily in a real implementation), a packet enters the dropper at
   its input and either its buffer is returned to a free buffer pool or
   the packet exits the dropper at the output.

   Alternatively, an Algorithmic Dropper can be thought of as invoking
   operations on a FIFO Queue which selectively remove a packet and
   return its buffer to the free buffer pool based on a discarding
   algorithm.  In this case, the operation could be modeled as being a
   side-effect on the FIFO upon which it operated, rather than as having
   a discrete input and output.  This treatment is equivalent and we
   choose the one described in the previous paragraph for this model.

   One of the primary characteristics of an Algorithmic Dropper is the
   choice of which packet (if any) is to be dropped: for the purposes of
   this model, we restrict the packet selection choices to one of the
   following and we indicate the choice by the relative positions of
   Algorithmic Dropper and FIFO Queue elements in the model:

   a) selection of a packet that is about to be added to the tail of a
      queue (a "Tail Dropper"): the output of the Algorithmic Dropper
      element is connected to the input of the relevant FIFO Queue
      element.

   b) a packet that is currently at the head of a queue (a "Head
      Dropper"): the output of the FIFO Queue element is connected to
      the input of the Algorithmic Dropper element.



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   Other packet selection methods could be added to this model in the
   form of a different type of datapath element.

   The Algorithmic Dropper is modeled as having a single input.  It is
   possible that packets which were classified differently by a
   Classifier in this TCB will end up passing through the same dropper.
   The dropper's algorithm may need to apply different calculations
   based on characteristics of the incoming packet (e.g., its DSCP).  So
   there is a need, in implementations of this model, to be able to
   relate information about which classifier element was matched by a
   packet from a Classifier to an Algorithmic Dropper.  In the rare
   cases where this is required, the chosen model is to insert another
   Classifier element at this point in the flow and for it to feed into
   multiple Algorithmic Dropper elements, each one implementing a drop
   calculation that is independent of any classification keys of the
   packet: this will likely require the creation of a new TCB to contain
   the Classifier and the Algorithmic Dropper elements.

      NOTE: There are many other formulations of a model that could
      represent this linkage that are different from the one described
      above: one formulation would have been to have a pointer from one
      of the drop probability calculation algorithms inside the dropper
      to the original Classifier element that selects this algorithm.
      Another way would have been to have multiple "inputs" to the
      Algorithmic Dropper element fed from the preceding elements,
      leading eventually back to the Classifier elements that matched
      the packet.  Yet another formulation might have been for the
      Classifier to (logically) include some sort of "classification
      identifier" along with the packet along its path, for use by any
      subsequent element.  And yet another could have been to include a
      classifier inside the dropper, in order for it to pick out the
      drop algorithm to be applied.  These other approaches could be
      used by implementations but were deemed to be less clear than the
      approach taken here.

   An Algorithmic Dropper, an example of which is illustrated in Figure
   5, has one or more triggers that cause it to make a decision whether
   or not to drop one (or possibly more than one) packet.  A trigger may
   be internal (the arrival of a packet at the input to the dropper) or
   it may be external (resulting from one or more state changes at
   another element, such as a FIFO Queue depth crossing a threshold or a
   scheduling event).  It is likely that an instantaneous FIFO depth
   will need to be smoothed over some averaging interval before being
   used as a useful trigger.  Some dropping algorithms may require
   several trigger inputs feeding back from events elsewhere in the
   system (e.g., depth-smoothing functions that calculate averages over
   more than one time interval).




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              +------------------+      +-----------+
              | +-------+        |  n   |smoothing  |
              | |trigger|<----------/---|function(s)|
              | |calc.  |        |      |(optional) |
              | +-------+        |      +-----------+
              |     |            |          ^
              |     v            |          |Depth
     Input    | +-------+ no     |      ------------+   to Scheduler
     ---------->|discard|-------------->    |x|x|x|x|------->
              | |   ?   |        |      ------------+
              | +-------+        |           FIFO
              |    |yes          |
              |  | | |           |
              |  | v | count +   |
              |  +---+ bit-bucket|
              +------------------+
              Algorithmic
              Dropper

      Figure 5. Example of Algorithmic Dropper from Tail of a Queue

   A trigger may be a boolean combination of events (e.g., a FIFO depth
   exceeding a threshold OR a buffer pool depth falling below a
   threshold).  It takes as its input some set of dynamic parameters
   (e.g., smoothed or instantaneous FIFO depth), and some set of static
   parameters (e.g., thresholds), and possibly other parameters
   associated with the packet.  It may also have internal state (e.g.,
   history of its past actions).  Note that, although an Algorithmic
   Dropper may require knowledge of data fields in a packet, as
   discovered by a Classifier in the same TCB, it may not modify the
   packet (i.e., it is not a marker).

   The result of the trigger calculation is that the dropping algorithm
   makes a decision on whether to forward or to discard a packet.  The
   discarding function is likely to keep counters regarding the
   discarded packets (there is no appropriate place here to include a
   Counter Action element).

   The example in Figure 5 also shows a FIFO Queue element from whose
   tail the dropping is to take place and whose depth characteristics
   are used by this Algorithmic Dropper.  It also shows where a depth-
   smoothing function might be included: smoothing functions are outside
   the scope of this document and are not modeled explicitly here, we
   merely indicate where they might be added.

   RED, RED-on-In-and-Out (RIO) and Drop-on-threshold are examples of
   dropping algorithms.  Tail-dropping and head-dropping are effected by
   the location of the Algorithmic Dropper element relative to the FIFO



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   Queue element.  As an example, a dropper using a RIO algorithm might
   be represented using 2 Algorithmic Droppers with the following
   parameters:

      AlgorithmicDropper1: (for in-profile traffic)
      Type:                   AlgorithmicDropper
      Discipline:             RED
      Trigger:                Internal
      Output:                 Fifo1
      MinThresh:              Fifo1.Depth > 20 kbyte
      MaxThresh:              Fifo1.Depth > 30 kbyte
      SampleWeight            .002
      MaxDropProb             1%

      AlgorithmicDropper2: (for out-of-profile traffic)
      Type:                   AlgorithmicDropper
      Discipline:             RED
      Trigger:                Internal
      Output:                 Fifo1
      MinThresh:              Fifo1.Depth > 10 kbyte
      MaxThresh:              Fifo1.Depth > 20 kbyte
      SampleWeight            .002
      MaxDropProb             2%

   Another form of Algorithmic Dropper, a threshold-dropper, might be
   represented using the following parameters:

      AlgorithmicDropper3:
      Type:                   AlgorithmicDropper
      Discipline:             Drop-on-threshold
      Trigger:                Fifo2.Depth > 20 kbyte
      Output:                 Fifo1

7.2.  Sharing load among traffic streams using queuing

   Queues are used, in Differentiated Services, for a number of
   purposes.  In essence, they are simply places to store traffic until
   it is transmitted.  However, when several queues are used together in
   a queuing system, they can also achieve effects beyond that for given
   traffic streams.  They can be used to limit variation in delay or
   impose a maximum rate (shaping), to permit several streams to share a
   link in a semi-predictable fashion (load sharing), or to move
   variation in delay from some streams to other streams.

   Traffic shaping is often used to condition traffic, such that packets
   arriving in a burst will be "smoothed" and deemed conforming by
   subsequent downstream meters in this or other nodes.  In [DSARCH] a
   shaper is described as a queuing element controlled by a meter which



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   defines its temporal profile.  However, this representation of a
   shaper differs substantially from typical shaper implementations.

   In the model described here, a shaper is realized by using a non-
   work-conserving Scheduler.  Some implementations may elect to have
   queues whose sole purpose is shaping, while others may integrate the
   shaping function with other buffering, discarding, and scheduling
   associated with access to a resource.  Shapers operate by delaying
   the departure of packets that would be deemed non-conforming by a
   meter configured to the shaper's maximum service rate profile.  The
   packet is scheduled to depart no sooner than such time that it would
   become conforming.

7.2.1.  Load Sharing

   Load sharing is the traditional use of queues and was theoretically
   explored by Floyd & Jacobson [FJ95], although it has been in use in
   communications systems since the 1970's.

   [DSARCH] discusses load sharing as dividing an interface among
   traffic classes predictably, or applying a minimum rate to each of a
   set of traffic classes, which might be measured as an absolute lower
   bound on the rate a traffic stream achieves or a fraction of the rate
   an interface offers.  It is generally implemented as some form of
   weighted queuing algorithm among a set of FIFO queues i.e., a WFQ
   scheme.  This has interesting side-effects.

   A key effect sought is to ensure that the mean rate the traffic in a
   stream experiences is never lower than some threshold when there is
   at least that much traffic to send.  When there is less traffic than
   this, the queue tends to be starved of traffic, meaning that the
   queuing system will not delay its traffic by very much.  When there
   is significantly more traffic and the queue starts filling, packets
   in this class will be delayed significantly more than traffic in
   other classes that are under-using their available capacity.  This
   form of queuing system therefore tends to move delay and variation in
   delay from under-used classes of traffic to heavier users, as well as
   managing the rates of the traffic streams.

   A side-effect of a WRR or WFQ implementation is that between any two
   packets in a given traffic class, the scheduler may emit one or more
   packets from each of the other classes in the queuing system.  In
   cases where average behavior is in view, this is perfectly
   acceptable.  In cases where traffic is very intolerant of jitter and
   there are a number of competing classes, this may have undesirable
   consequences.





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7.2.2.  Traffic Priority

   Traffic Prioritization is a special case of load sharing, wherein a
   certain traffic class is deemed so jitter-intolerant that if it has
   traffic present, that traffic must be sent at the earliest possible
   time.  By extension, several priorities might be defined, such that
   traffic in each of several classes is given preferential service over
   any traffic of a lower class.  It is the obvious implementation of IP
   Precedence as described in [RFC 791], of 802.1p traffic classes
   [802.1D], and other similar technologies.

   Priority is often abused in real networks; people tend to think that
   traffic which has a high business priority deserves this treatment
   and talk more about the business imperatives than the actual
   application requirements.  This can have severe consequences;
   networks have been configured which placed business-critical traffic
   at a higher priority than routing-protocol traffic, resulting in
   collapse of the network's management or control systems.  However, it
   may have a legitimate use for services based on an Expedited
   Forwarding (EF) PHB, where it is absolutely sure, thanks to policing
   at all possible traffic entry points, that a traffic stream does not
   abuse its rate and that the application is indeed jitter-intolerant
   enough to merit this type of handling.  Note that, even in cases with
   well-policed ingress points, there is still the possibility of
   unexpected traffic loops within an un-policed core part of the
   network causing such collapse.

8.  Traffic Conditioning Blocks (TCBs)

   The Classifier, Meter, Action, Algorithmic Dropper, Queue and
   Scheduler functional datapath elements described above can be
   combined into Traffic Conditioning Blocks (TCBs).  A TCB is an
   abstraction of a set of functional datapath elements that may be used
   to facilitate the definition of specific traffic conditioning
   functionality (e.g., it might be likened to a template which can be
   replicated multiple times for different traffic streams or different
   customers).  It has no likely physical representation in the
   implementation of the data path: it is invented purely as an
   abstraction for use by management tools.

   This model describes the configuration and management of a Diffserv
   interface in terms of a TCB that contains, by definition, zero or
   more Classifier, Meter, Action, Algorithmic Dropper, Queue and
   Scheduler elements.  These elements are arranged arbitrarily
   according to the policy being expressed, but always in the order
   here.  Traffic may be classified; classified traffic may be metered;
   each stream of traffic identified by a combination of classifiers and
   meters may have some set of actions performed on it, followed by drop



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   algorithms; packets of the traffic stream may ultimately be stored
   into a queue and then be scheduled out to the next TCB or physical
   interface.  It is permissible to omit elements or include null
   elements of any type, or to concatenate multiple functional datapath
   elements of the same type.

   When the Diffserv treatment for a given packet needs to have such
   building blocks repeated, this is performed by cascading multiple
   TCBs:  an output of one TCB may drive the input of a succeeding one.
   For example, consider the case where traffic of a set of classes is
   shaped to a set of rates, but the total output rate of the group of
   classes must also be limited to a rate.  One might imagine a set of
   network news feeds, each with a certain maximum rate, and a policy
   that their aggregate may not exceed some figure.  This may be simply
   accomplished by cascading two TCBs.  The first classifies the traffic
   into its separate feeds and queues each feed separately.  The feeds
   (or a subset of them) are now fed into a second TCB, which places all
   input (these news feeds) into a single queue with a certain maximum
   rate.  In implementation, one could imagine this as the several
   literal queues, a CBQ or WFQ system with an appropriate (and complex)
   weighting scheme, or a number of other approaches.  But they would
   have the same externally measurable effect on the traffic as if they
   had been literally implemented with separate TCBs.

8.1.  TCB

   A generalized TCB might consist of the following stages:

      -  Classification stage

      -  Metering stage

      -  Action stage (involving Markers, Absolute Droppers, Counters,
         and Multiplexors)

      -  Queuing stage (involving Algorithmic Droppers, Queues, and
         Schedulers)

   where each stage may consist of a set of parallel datapaths
   consisting of pipelined elements.

   A Classifier or a Meter is typically a 1:N element, an Action,
   Algorithmic Dropper, or Queue is typically a 1:1 element and a
   Scheduler is a N:1 element.  A complete TCB should, however, result
   in a 1:1 or 1:N abstract element.  Note that the fan-in or fan-out of
   an element is not an important defining characteristic of this
   taxonomy.




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8.1.1.  Building blocks for Queuing

   Some particular rules are applied to the ordering of elements within
   a Queuing stage within a TCB: elements of the same type may appear
   more than once, either in parallel or in series.  Typically, a
   queuing stage will have relatively many elements in parallel and few
   in series.  Iteration and recursion are not supported constructs (the
   elements are arranged in an acyclic graph).  The following inter-
   connections of elements are allowed:

      -  The input of a Queue may be the input of the queuing block, or
         it may be connected to the output of an Algorithmic Dropper, or
         to an output of a Scheduler.

      -  Each input of a Scheduler may be connected to the output of a
         Queue, to the output of an Algorithmic Dropper, or to the
         output of another Scheduler.

      -  The input of an Algorithmic Dropper may be the first element of
         the queuing stage, the output of another Algorithmic Dropper,
         or it may be connected to the output of a Queue (to indicate
         head-dropping).

      -  The output of the queuing block may be the output of a Queue,
         an Algorithmic Dropper, or a Scheduler.

   Note, in particular, that Schedulers may operate in series such so
   that a packet at the head of a Queue feeding the concatenated
   Schedulers is serviced only after all of the scheduling criteria are
   met.  For example, a Queue which carries EF traffic streams may be
   served first by a non-work-conserving Scheduler to shape the stream
   to a maximum rate, then by a work-conserving Scheduler to mix EF
   traffic streams with other traffic streams.  Alternatively, there
   might be a Queue and/or a dropper between the two Schedulers.

   Note also that some non-sensical scenarios (e.g., a Queue preceding
   an Algorithmic Dropper, directly feeding into another Queue), are
   prohibited.

8.2.  An Example TCB

   A SLS is presumed to have been negotiated between the customer and
   the provider which specifies the handling of the customer's traffic,
   as defined by a TCS) by the provider's network.  The agreement might
   be of the following form:






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      DSCP     PHB   Profile     Treatment
      ----     ---   -------     ----------------------
      001001   EF    Profile4    Discard non-conforming.
      001100   AF11  Profile5    Shape to profile, tail-drop when full.
      001101   AF21  Profile3    Re-mark non-conforming to DSCP 001000,
                                 tail-drop when full.
      other    BE    none        Apply RED-like dropping.

   This SLS specifies that the customer may submit packets marked for
   DSCP 001001 which will get EF treatment so long as they remain
   conforming to Profile4, which will be discarded if they exceed this
   profile.  The discarded packets are counted in this example, perhaps
   for use by the provider's sales department in convincing the customer
   to buy a larger SLS.  Packets marked for DSCP 001100 will be shaped
   to Profile5 before forwarding.  Packets marked for DSCP 001101 will
   be metered to Profile3 with non-conforming packets "downgraded" by
   being re-marked with a DSCP of 001000.  It is implicit in this
   agreement that conforming packets are given the PHB originally
   indicated by the packets' DSCP field.

   Figures 6 and 7 illustrates a TCB that might be used to handle this
   SLS at an ingress interface at the customer/provider boundary.

   The Classification stage of this example consists of a single BA
   classifier.  The BA classifier is used to separate traffic based on
   the Diffserv service level requested by the customer (as indicated by
   the DSCP in each submitted packet's IP header).  We illustrate three
   DSCP filter values: A, B, and C. The 'X' in the BA classifier is a
   wildcard filter that matches every packet not otherwise matched.

   The path for DSCP 001100 proceeds directly to Dropper1 whilst the
   paths for DSCP 001001 and 001101 include a metering stage.  All other
   traffic is passed directly on to Dropper3.  There is a separate meter
   for each set of packets corresponding to classifier outputs A and C.
   Each meter uses a specific profile, as specified in the TCS, for the
   corresponding Diffserv service level.  The meters in this example
   each indicate one of two conformance levels: conforming or non-
   conforming.

   Following the Metering stage is an Action stage in some of the
   branches.  Packets submitted for DSCP 001001 (Classifier output A)
   that are deemed non-conforming by Meter1 are counted and discarded
   while packets that are conforming are passed on to Queue1.  Packets
   submitted for DSCP 001101 (Classifier output C) that are deemed non-
   conforming by Meter2 are re-marked and then both conforming and non-
   conforming packets are multiplexed together before being passed on to
   Dropper2/Queue3.




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   The Algorithmic Dropping, Queuing and Scheduling stages are realized
   as follows, illustrated in figure 7.  Note that the figure does not
   show any of the implicit control linkages between elements that allow
   e.g., an Algorithmic Dropper to sense the current state of a
   succeeding Queue.

                         +-----+
                         |    A|---------------------------> to Queue1
                      +->|     |
                      |  |    B|--+  +-----+    +-----+
                      |  +-----+  |  |     |    |     |
                      |  Meter1   +->|     |--->|     |
                      |              |     |    |     |
                      |              +-----+    +-----+
                      |              Counter1   Absolute
submitted +-----+     |                         Dropper1
traffic   |    A|-----+
--------->|    B|--------------------------------------> to AlgDropper1
          |    C|-----+
          |    X|--+  |
          +-----+  |  |  +-----+                +-----+
        Classifier1|  |  |    A|--------------->|A    |
           (BA)    |  +->|     |                |     |--> to AlgDrop2
                   |     |    B|--+  +-----+ +->|B    |
                   |     +-----+  |  |     | |  +-----+
                   |     Meter2   +->|     |-+    Mux1
                   |                 |     |
                   |                 +-----+
                   |                 Marker1
                   +-----------------------------------> to AlgDropper3

     Figure 6:  An Example Traffic Conditioning Block (Part 1)

   Conforming DSCP 001001 packets from Meter1 are passed directly to
   Queue1: there is no way, with configuration of the following
   Scheduler to match the metering, for these packets to overflow the
   depth of Queue1, so there is no requirement for dropping at this
   point.  Packets marked for DSCP 001100 must be passed through a
   tail-dropper, AlgDropper1, which serves to limit the depth of the
   following queue, Queue2: packets that arrive to a full queue will be
   discarded.  This is likely to be an error case: the customer is
   obviously not sticking to its agreed profile.  Similarly, all packets
   from the original DSCP 001101 stream (some may have been re-marked by
   this stage) are passed to AlgDropper2 and Queue3.  Packets marked for
   all other DSCPs are passed to AlgDropper3 which is a RED-like
   Algorithmic Dropper: based on feedback of the current depth of
   Queue4, this dropper is supposed to discard enough packets from its
   input stream to keep the queue depth under control.



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   These four Queue elements are then serviced by a Scheduler element
   Scheduler1: this must be configured to give each of its inputs an
   appropriate priority and/or bandwidth share.  Inputs A and C are
   given guarantees of bandwidth, as appropriate for the contracted
   profiles.  Input B is given a limit on the bandwidth it can use
   (i.e., a non-work-conserving discipline) in order to achieve the
   desired shaping of this stream.  Input D is given no limits or
   guarantees but a lower priority than the other queues, appropriate
   for its best-effort status.  Traffic then exits the Scheduler in a
   single orderly stream.

   The interconnections of the TCB elements illustrated in Figures 6 and
   7 can be represented textually as follows:

        TCB1:

        Classifier1:
        FilterA:             Meter1
        FilterB:             Dropper1
        FilterC:             Meter2
        Default:             Dropper3


      from Meter1                     +-----+
      ------------------------------->|     |----+
                                      |     |    |
                                      +-----+    |
                                      Queue1     |
                                                 |  +-----+
      from Classifier1 +-----+        +-----+    +->|A    |
      ---------------->|     |------->|     |------>|B    |------->
                       |     |        |     |  +--->|C    |  exiting
                       +-----+        +-----+  | +->|D    |  traffic
                       AlgDropper1    Queue2   | |  +-----+
                                               | |  Scheduler1
      from Mux1        +-----+        +-----+  | |
      ---------------->|     |------->|     |--+ |
                       |     |        |     |    |
                       +-----+        +-----+    |
                       AlgDropper2    Queue3     |
                                                 |
      from Classifier1 +-----+        +-----+    |
      ---------------->|     |------->|     |----+
                       |     |        |     |
                       +-----+        +-----+
                       AlgDropper3    Queue4

        Figure 7: An Example Traffic Conditioning Block (Part 2)



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        Meter1:
        Type:                AverageRate
        Profile:             Profile4
        ConformingOutput:    Queue1
        NonConformingOutput: Counter1

        Counter1:
        Output:              AbsoluteDropper1

        Meter2:
        Type:                AverageRate
        Profile:             Profile3
        ConformingOutput:    Mux1.InputA
        NonConformingOutput: Marker1

        Marker1:
        Type:                DSCPMarker
        Mark:                001000
        Output:              Mux1.InputB

        Mux1:
        Output:              Dropper2

        AlgDropper1:
        Type:                AlgorithmicDropper
        Discipline:          Drop-on-threshold
        Trigger:             Queue2.Depth > 10kbyte
        Output:              Queue2

        AlgDropper2:
        Type:                AlgorithmicDropper
        Discipline:          Drop-on-threshold
        Trigger:             Queue3.Depth > 20kbyte
        Output:              Queue3

        AlgDropper3:
        Type:                AlgorithmicDropper
        Discipline:          RED93
        Trigger:             Internal
        Output:              Queue3
        MinThresh:           Queue3.Depth > 20 kbyte
        MaxThresh:           Queue3.Depth > 40 kbyte
           <other RED parms too>








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        Queue1:
        Type:                FIFO
        Output:              Scheduler1.InputA

        Queue2:
        Type:                FIFO
        Output:              Scheduler1.InputB

        Queue3:
        Type:                FIFO
        Output:              Scheduler1.InputC

        Queue4:
        Type:                FIFO
        Output:              Scheduler1.InputD

        Scheduler1:
        Type:                Scheduler4Input
        InputA:
        MaxRateProfile:      none
        MinRateProfile:      Profile4
        Priority:            20
        InputB:
        MaxRateProfile:      Profile5
        MinRateProfile:      none
        Priority:            40
        InputC:
        MaxRateProfile:      none
        MinRateProfile:      Profile3
        Priority:            20
        InputD:
        MaxRateProfile:      none
        MinRateProfile:      none
        Priority:            10

8.3.  An Example TCB to Support Multiple Customers

   The TCB described above can be installed on an ingress interface to
   implement a provider/customer TCS if the interface is dedicated to
   the customer.  However, if a single interface is shared between
   multiple customers, then the TCB above will not suffice, since it
   does not differentiate among traffic from different customers.  Its
   classification stage uses only BA classifiers.

   The configuration is readily modified to support the case of multiple
   customers per interface, as follows.  First, a TCB is defined for
   each customer to reflect the TCS with that customer: TCB1, defined
   above is the TCB for customer 1.  Similar elements are created for



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   TCB2 and for TCB3 which reflect the agreements with customers 2 and 3
   respectively.  These 3 TCBs may or may not contain similar elements
   and parameters.

   Finally, a classifier is added to the front end to separate the
   traffic from the three different customers.  This forms a new TCB,
   TCB4, which is illustrated in Figure 8.

   A representation of this multi-customer TCB might be:

      TCB4:

      Classifier4:
      Filter1:     to TCB1
      Filter2:     to TCB2
      Filter3:     to TCB3
      No Match:    AbsoluteDropper4

      AbsoluteDropper4:
      Type:                AbsoluteDropper

      TCB1:
      (as defined above)

      TCB2:
      (similar to TCB1, perhaps with different
       elements or numeric parameters)

      TCB3:
      (similar to TCB1, perhaps with different
       elements or numeric parameters)

   and the filters, based on each customer's source MAC address, could
   be defined as follows:

      Filter1:

      submitted +-----+
      traffic   |    A|--------> TCB1
      --------->|    B|--------> TCB2
                |    C|--------> TCB3
                |    X|------+   +-----+
                +-----+      +-->|     |
                Classifier4      +-----+
                                 AbsoluteDrop4

      Figure 8: An Example of a Multi-Customer TCB




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      Type:        MacAddress
      SrcValue:    01-02-03-04-05-06 (source MAC address of customer 1)
      SrcMask:     FF-FF-FF-FF-FF-FF
      DestValue:   00-00-00-00-00-00
      DestMask:    00-00-00-00-00-00

      Filter2:
      (similar to Filter1 but with customer 2's source MAC address as
       SrcValue)

      Filter3:
      (similar to Filter1 but with customer 3's source MAC address as
       SrcValue)

   In this example, Classifier4 separates traffic submitted from
   different customers based on the source MAC address in submitted
   packets.  Those packets with recognized source MAC addresses are
   passed to the TCB implementing the TCS with the corresponding
   customer.  Those packets with unrecognized source MAC addresses are
   passed to a dropper.

   TCB4 has a Classifier stage and an Action element stage performing
   dropping of all unmatched traffic.

8.4.  TCBs Supporting Microflow-based Services

   The TCB illustrated above describes a configuration that might be
   suitable for enforcing a SLS at a router's ingress.  It assumes that
   the customer marks its own traffic for the appropriate service level.
   It then limits the rate of aggregate traffic submitted at each
   service level, thereby protecting the resources of the Diffserv
   network.  It does not provide any isolation between the customer's
   individual microflows.

   A more complex example might be a TCB configuration that offers
   additional functionality to the customer.  It recognizes individual
   customer microflows and marks each one independently.  It also
   isolates the customer's individual microflows from each other in
   order to prevent a single microflow from seizing an unfair share of
   the resources available to the customer at a certain service level.
   This is illustrated in Figure 9.

   Suppose that the customer has an SLS which specifies 2 service
   levels, to be identified to the provider by DSCP A and DSCP B.
   Traffic is first directed to a MF classifier which classifies traffic
   based on miscellaneous classification criteria, to a granularity
   sufficient to identify individual customer microflows.  Each
   microflow can then be marked for a specific DSCP The metering



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   elements limit the contribution of each of the customer's microflows
   to the service level for which it was marked.  Packets exceeding the
   allowable limit for the microflow are dropped.

                     +-----+   +-----+
    Classifier1      |     |   |     |---------------+
        (MF)      +->|     |-->|     |     +-----+   |
      +-----+     |  |     |   |     |---->|     |   |
      |    A|------  +-----+   +-----+     +-----+   |
   -->|    B|-----+  Marker1   Meter1      Absolute  |
      |    C|---+ |                        Dropper1  |   +-----+
      |    X|-+ | |  +-----+   +-----+               +-->|A    |
      +-----+ | | |  |     |   |     |------------------>|B    |--->
              | | +->|     |-->|     |     +-----+   +-->|C    | to TCB2
              | |    |     |   |     |---->|     |   |   +-----+
              | |    +-----+   +-----+     +-----+   |    Mux1
              | |    Marker2   Meter2      Absolute  |
              | |                          Dropper2  |
              | |    +-----+   +-----+               |
              | |    |     |   |     |---------------+
              | |--->|     |-->|     |     +-----+
              |      |     |   |     |---->|     |
              |      +-----+   +-----+     +-----+
              |      Marker3   Meter3      Absolute
              |                            Dropper3
              V etc.

      Figure 9: An Example of a Marking and Traffic Isolation TCB

   This TCB could be formally specified as follows:

      TCB1:
      Classifier1: (MF)
      FilterA:             Marker1
      FilterB:             Marker2
      FilterC:             Marker3
      etc.

      Marker1:
      Output:              Meter1

      Marker2:
      Output:              Meter2

      Marker3:
      Output:              Meter3





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      Meter1:
      ConformingOutput:    Mux1.InputA
      NonConformingOutput: AbsoluteDropper1

      Meter2:
      ConformingOutput:    Mux1.InputB
      NonConformingOutput: AbsoluteDropper2

      Meter3:
      ConformingOutput:    Mux1.InputC
      NonConformingOutput: AbsoluteDropper3

      etc.

      Mux1:
      Output:              to TCB2

   Note that the detailed traffic element declarations are not shown
   here.  Traffic is either dropped by TCB1 or emerges marked for one of
   two DSCPs.  This traffic is then passed to TCB2 which is illustrated
   in Figure 10.

   TCB2 could then be specified as follows:

      Classifier2: (BA)
      FilterA:               Meter5
      FilterB:               Meter6


                     +-----+
                     |     |---------------> to Queue1
                  +->|     |     +-----+
        +-----+   |  |     |---->|     |
        |    A|---+  +-----+     +-----+
      ->|     |       Meter5     AbsoluteDropper4
        |    B|---+  +-----+
        +-----+   |  |     |---------------> to Queue2
      Classifier2 +->|     |     +-----+
         (BA)        |     |---->|     |
                     +-----+     +-----+
                      Meter6     AbsoluteDropper5

      Figure 10: Additional Example: TCB2

      Meter5:
      ConformingOutput:      Queue1
      NonConformingOutput:   AbsoluteDropper4




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      Meter6:
      ConformingOutput:      Queue2
      NonConformingOutput:   AbsoluteDropper5

8.5.  Cascaded TCBs

   Nothing in this model prevents more complex scenarios in which one
   microflow TCB precedes another (e.g., for TCBs implementing separate
   TCSs for the source and for a set of destinations).

9.  Security Considerations

   Security vulnerabilities of Diffserv network operation are discussed
   in [DSARCH].  This document describes an abstract functional model of
   Diffserv router elements.  Certain denial-of-service attacks such as
   those resulting from resource starvation may be mitigated by
   appropriate configuration of these router elements; for example, by
   rate limiting certain traffic streams or by authenticating traffic
   marked for higher quality-of-service.

   There may be theft-of-service scenarios where a malicious host can
   exploit a loose token bucket policer to obtain slightly better QoS
   than that committed in the TCS.

10.  Acknowledgments

   Concepts, terminology, and text have been borrowed liberally from
   [POLTERM], as well as from other IETF work on MIBs and policy-
   management.  We wish to thank the authors of some of those documents:
   Fred Baker, Michael Fine, Keith McCloghrie, John Seligson, Kwok Chan,
   Scott Hahn, and Andrea Westerinen for their contributions.

   This document has benefited from the comments and suggestions of
   several participants of the Diffserv working group, particularly
   Shahram Davari, John Strassner, and Walter Weiss.  This document
   could never have reached this level of rough consensus without the
   relentless pressure of the co-chairs Brian Carpenter and Kathie
   Nichols, for which the authors are grateful.

11.  References

   [AF-PHB]    Heinanen, J., Baker, F., Weiss, W. and J. Wroclawski,
               "Assured Forwarding PHB Group", RFC 2597, June 1999.

   [DSARCH]    Carlson, M., Weiss, W., Blake, S., Wang, Z., Black, D.
               and E. Davies, "An Architecture for Differentiated
               Services", RFC 2475, December 1998.




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   [DSFIELD]   Nichols, K., Blake, S., Baker, F. and D. Black,
               "Definition of the Differentiated Services Field (DS
               Field) in the IPv4 and IPv6 Headers", RFC 2474, December
               1998.

   [DSMIB]     Baker, F., Smith, A., and K. Chan, "Management
               Information Base for the Differentiated Services
               Architecture", RFC 3289, May 2002.

   [E2E]       Bernet, Y., Yavatkar, R., Ford, P., Baker, F., Zhang, L.,
               Speer, M., Nichols, K., Braden, R., Davie, B.,
               Wroclawski, J. and E. Felstaine, "A Framework for
               Integrated Services Operation over Diffserv Networks",
               RFC 2998, November 2000.

   [EF-PHB]    Davie, B., Charny, A., Bennett, J.C.R., Benson, K., Le
               Boudec, J.Y., Courtney, W., Davari, S., Firoiu, V. and D.
               Stiliadis, "An Expedited Forwarding PHB (Per-Hop
               Behavior)", RFC 3246, March 2002.

   [FJ95]      Floyd, S. and V. Jacobson, "Link Sharing and Resource
               Management Models for Packet Networks", IEEE/ACM
               Transactions on Networking, Vol. 3 No. 4, August 1995l.

   [INTSERV]   Braden, R., Clark, D. and S. Shenker, "Integrated
               Services in the Internet Architecture: an Overview", RFC
               1633, June 1994.

   [NEWTERMS]  Grossman, D., "New Terminology and Clarifications for
               Diffserv", RFC 3260, April, 2002

   [PDBDEF]    K. Nichols and B. Carpenter, "Definition of
               Differentiated Services Per Domain Behaviors and Rules
               for Their Specification", RFC 3086, April 2001.

   [POLTERM]   Westerinen, A., Schnizlein, J., Strassner, J., Scherling,
               M., Quinn, B., Herzog, S., Huynh, A., Carlson, M., Perry,
               J. and S. Waldbusser, "Policy Terminology", RFC 3198,
               November 2001.

   [QOSDEVMOD] Strassner, J., Westerinen, A. and B. Moore, "Information
               Model for Describing Network Device QoS Mechanisms", Work
               in Progress.








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   [QUEUEMGMT] Braden, R., Clark, D., Crowcroft, J., Davie, B., Deering,
               S., Estrin, D., Floyd, S., Jacobson, V., Minshall, C.,
               Partridge, C., Peterson, L., Ramakrishnan, K., Shenker,
               S., Wroclawski, J. and L. Zhang, "Recommendations on
               Queue Management and Congestion Avoidance in the
               Internet", RFC 2309, April 1998.

   [SRTCM]     Heinanen, J. and R. Guerin, "A Single Rate Three Color
               Marker", RFC 2697, September 1999.

   [TRTCM]     Heinanen, J. and R. Guerin, "A Two Rate Three Color
               Marker", RFC 2698, September 1999.

   [VIC]       McCanne, S. and Jacobson, V., "vic: A Flexible Framework
               for Packet Video", ACM Multimedia '95, November 1995, San
               Francisco, CA, pp. 511-522.
               <ftp://ftp.ee.lbl.gov/papers/vic-mm95.ps.Z>

   [802.1D]   "Information technology - Telecommunications and
               information exchange between systems - Local and
               metropolitan area networks - Common specifications - Part
               3: Media Access Control (MAC) Bridges:  Revision.  This
               is a revision of ISO/IEC 10038: 1993, 802.1j-1992 and
               802.6k-1992.  It incorporates P802.11c, P802.1p and
               P802.12e.", ISO/IEC 15802-3: 1998.


























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Appendix A. Discussion of Token Buckets and Leaky Buckets

   "Leaky bucket" and/or "Token Bucket" models are used to describe rate
   control in several architectures, including Frame Relay, ATM,
   Integrated Services and Differentiated Services.  Both of these
   models are, by definition, theoretical relationships between some
   defined burst size, B, a rate, R, and a time interval, t:

                  R = B/t

   Thus, a token bucket or leaky bucket might specify an information
   rate of 1.2 Mbps with a burst size of 1500 bytes.  In this case, the
   token rate is 1,200,000 bits per second, the token burst is 12,000
   bits and the token interval is 10 milliseconds.  The specification
   says that conforming traffic will, in the worst case, come in 100
   bursts per second of 1500 bytes each and at an average rate not
   exceeding 1.2 Mbps.

A.1 Leaky Buckets

   A leaky bucket algorithm is primarily used for shaping traffic as it
   leaves an interface onto the network (handled under Queues and
   Schedulers in this model).  Traffic theoretically departs from an
   interface at a rate of one bit every so many time units (in the
   example, one bit every 0.83 microseconds) but, in fact, departs in
   multi-bit units (packets) at a rate approximating the theoretical, as
   measured over a longer interval.  In the example, it might send one
   1500 byte packet every 10 ms or perhaps one 500 byte packet every 3.3
   ms.  It is also possible to build multi-rate leaky buckets in which
   traffic departs from the interface at varying rates depending on
   recent activity or inactivity.

   Implementations generally seek as constant a transmission rate as
   achievable.  In theory, a 10 Mbps shaped transmission stream from an
   algorithmic implementation and a stream which is running at 10 Mbps
   because its bottleneck link has been a 10 Mbps Ethernet link should
   be indistinguishable.  Depending on configuration, the approximation
   to theoretical smoothness may vary by moving as much as an MTU from
   one token interval to another.  Traffic may also be jostled by other
   traffic competing for the same transmission resources.

A.2 Token Buckets

   A token bucket, on the other hand, measures the arrival rate of
   traffic from another device.  This traffic may originally have been
   shaped using a leaky bucket shaper or its equivalent.  The token
   bucket determines whether the traffic (still) conforms to the
   specification.  Multi-rate token buckets (e.g., token buckets with



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   both a peak rate and a mean rate, and sometimes more) are commonly
   used, such as those described in [SRTCM] and [TRTCM].  In this case,
   absolute smoothness is not expected, but conformance to one or more
   of the specified rates is.

   Simplistically, a data stream is said to conform to a simple token
   bucket parameterized by a {R, B} if the system receives in any time
   interval, t, at most, an amount of data not exceeding (R * t) + B.

   For a multi-rate token bucket case, the data stream is said to
   conform if, for each of the rates, the stream conforms to the token-
   bucket profile appropriate for traffic of that class.  For example,
   received traffic that arrives pre-classified as one of the "excess"
   rates (e.g., AF12 or AF13 traffic for a device implementing the AF1x
   PHB) is only compared to the relevant "excess" token bucket profile.

A.3 Some Consequences

   The fact that Internet Protocol data is organized into variable
   length packets introduces some uncertainty in the conformance
   decision made by any downstream Meter that is attempting to determine
   conformance to a traffic profile that is theoretically designed for
   fixed-length units of data.

   When used as a leaky bucket shaper, the above definition interacts
   with clock granularity in ways one might not expect.  A leaky bucket
   releases a packet only when all of its bits would have been allowed:
   it does not borrow from future capacity.  If the clock is very fine
   grain, on the order of the bit rate or faster, this is not an issue.
   But if the clock is relatively slow (and millisecond or multi-
   millisecond clocks are not unusual in networking equipment), this can
   introduce jitter to the shaped stream.

   This leaves an implementor of a token bucket Meter with a dilemma.
   When the number of bandwidth tokens, b, left in the token bucket is
   positive but less than the size of the packet being operated on, L,
   one of three actions can be performed:

      (1)   The whole size of the packet can be subtracted from the
            bucket, leaving it negative, remembering that, when new
            tokens are next added to the bucket, the new token
            allocation, B, must be added to b rather than simply setting
            the bucket to "full".  This option potentially puts more
            than the desired burst size of data into this token bucket
            interval and correspondingly less into the next.  It does,
            however, keep the average amount accepted per token bucket
            interval equal to the token burst.  This approach accepts
            traffic if any one bit in the packet would have been



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            accepted and borrows up to one MTU of capacity from one or
            more subsequent intervals when necessary.  Such a token
            bucket meter implementation is said to offer "loose"
            conformance to the token bucket.

      (2)   Alternatively, the packet can be rejected and the amount of
            tokens in the bucket left unchanged (and maybe an attempt
            could be made to accept the packet under another threshold
            in another bucket), remembering that, when new tokens are
            next added to the bucket, the new token allocation, B, must
            be added to b rather than simply setting the bucket to
            "full".  This potentially puts less than the permissible
            burst size of data into this token bucket interval and
            correspondingly more into the next.  Like the first option,
            it keeps the average amount accepted per token bucket
            interval equal to the token burst.  This approach accepts
            traffic only if every bit in the packet would have been
            accepted and borrows up to one MTU of capacity from one or
            more previous intervals when necessary.  Such a token bucket
            meter implementation is said to offer "strict" (or perhaps
            "stricter") conformance to the token bucket.  This option is
            consistent with [SRTCM] and [TRTCM] and is often used in ATM
            and frame-relay implementations.

      (3)   The TB variable can be set to zero to account for the first
            part of the packet and the remainder of the packet size can
            be taken out of the next-colored bucket.  This, of course,
            has another bug:  the same packet cannot have both
            conforming and non-conforming components in the Diffserv
            architecture and so is not really appropriate here and we do
            not discuss this option further here.

            Unfortunately, the thing that cannot be done is exactly to
            fit the token burst specification with random sized packets:
            therefore token buckets in a variable length packet
            environment always have a some variance from theoretical
            reality.  This has also been observed in the ATM Guaranteed
            Frame Rate (GFR) service category specification and Frame
            Relay.  A number of observations may be made:

   o  Operationally, a token bucket meter is reasonable for traffic
      which has been shaped by a leaky bucket shaper or a serial line.
      However, traffic in the Internet is rarely shaped in that way: TCP
      applies no shaping to its traffic, but rather depends on longer-
      range ACK-clocking behavior to help it approximate a certain rate
      and explicitly sends traffic bursts during slow start,
      retransmission, and fast recovery.  Video-on-IP implementations
      such as [VIC] may have a leaky bucket shaper available to them,



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      but often do not, and simply enqueue the output of their codec for
      transmission on the appropriate interface.  As a result, in each
      of these cases, a token bucket meter may reject traffic in the
      short term (over a single token interval) which it would have
      accepted if it had a longer time in view and which it needs to
      accept for the application to work properly.  To work around this,
      the token interval, B/R, must approximate or exceed the RTT of the
      session(s) in question and the burst size, B, must accommodate the
      largest burst that the originator might send.

   o  The behavior of a loose token bucket is significantly different
      from the token bucket description for ATM and for Frame Relay.

   o  A loose token bucket does not accept packets while the token count
      is negative.  This means that, when a large packet has just
      borrowed tokens from the future, even a small incoming packet
      (e.g., a 40-byte TCP ACK/SYN) will not be accepted.  Therefore, if
      such a loose token bucket is configured with a burst size close to
      the MTU, some discrimination against smaller packets can take
      place: use of a larger burst size avoids this problem.

   o  The converse of the above is that a strict token bucket sometimes
      does not accept large packets when a loose one would do so.
      Therefore, if such a strict token bucket is configured with a
      burst size close to the MTU, some discrimination against larger
      packets can take place: use of a larger burst size avoids this
      problem.

   o  In real-world deployments, MTUs are often larger than the burst
      size offered by a link-layer network service provider.  If so then
      it is possible that a strict token bucket meter would find that
      traffic never matches the specified profile: this may be avoided
      by not allowing such a specification to be used.  This situation
      cannot arise with a loose token bucket since the smallest burst
      size that can be configured is 1 bit, by definition limiting a
      loose token bucket to having a burst size of greater than one MTU.

   o  Both strict token bucket specifications, as specified in [SRTCM]
      and [TRTCM], and loose ones, are subject to a persistent under-
      run.  These accumulate burst capacity over time, up to the maximum
      burst size.  Suppose that the maximum burst size is exactly the
      size of the packets being sent - which one might call the
      "strictest" token bucket implementation.  In such a case, when one
      packet has been accepted, the token depth becomes zero and starts
      to accumulate again.  If the next packet is received any time
      earlier than a token interval later, it will not be accepted.  If
      the next packet arrives exactly on time, it will be accepted and
      the token depth again set to zero.  If it arrives later, however,



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      accumulation of tokens will have stopped because it is capped by
      the maximum burst size: during the interval between the bucket
      becoming full and the actual arrival of the packet, no new tokens
      are added.  As a result, jitter that accumulates across multiple
      hops in the network conspires against the algorithm to reduce the
      actual acceptance rate.  Thus it usually makes sense to set the
      maximum token bucket size somewhat greater than the MTU in order
      to absorb some of the jitter and allow a practical acceptance rate
      more in line with the desired theoretical rate.

A.4 Mathematical Definition of Strict Token Bucket Conformance

   The strict token bucket conformance behavior defined in [SRTCM] and
   [TRTCM] is not mandatory for compliance with any current Diffserv
   standards, but we give here a mathematical definition of two-
   parameter token bucket operation which is consistent with those
   documents and which can also be used to define a shaping profile.

   Define a token bucket with bucket size B, token accumulation rate R
   and instantaneous token occupancy b(t).  Assume that b(0) = B.  Then
   after an arbitrary interval with no packet arrivals, b(t) will not
   change since the bucket is already full of tokens.

   Assume a packet of size L bytes arrives at time t'.  The bucket
   occupancy is still B.  Then, as long as L <= B, the packet conforms
   to the meter, and afterwards

                  b(t') = B - L.

   Assume now an interval delta_t = t - t' elapses before the next
   packet arrives, of size L' <= B.  Just before this, at time t-, the
   bucket has accumulated delta_t*R tokens over the interval, up to a
   maximum of B tokens so that:

                  b(t-) = min{ B, b(t') + delta_t*R }

   For a strict token bucket, the conformance test is as follows:

      if (b(t-) - L' >= 0) {
          /* the packet conforms */
          b(t) = b(t-) - L';
      }
      else {
          /* the packet does not conform */
          b(t) = b(t-);
      }





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   This function can also be used to define a shaping profile.  If a
   packet of size L arrives at time t, it will be eligible for
   transmission at time te given as follows (we still assume L <= B):

                  te = max{ t, t" }

   where t" = (L - b(t') + t'*R) / R and b(t") = L, the time when L
   credits have accumulated in the bucket, and when the packet would
   conform if the token bucket were a meter. te != t" only if t > t".

   A mathematical definition along these lines for loose token bucket
   conformance is left as an exercise for the reader.

Authors' Addresses

   Yoram Bernet
   Microsoft
   One Microsoft Way
   Redmond, WA  98052

   Phone:  +1 425 936 9568
   EMail: ybernet@msn.com

   Steven Blake
   Ericsson
   920 Main Campus Drive, Suite 500
   Raleigh, NC  27606

   Phone:  +1 919 472 9913
   EMail: steven.blake@ericsson.com

   Daniel Grossman
   Motorola Inc.
   20 Cabot Blvd.
   Mansfield, MA  02048

   Phone:  +1 508 261 5312
   EMail: dan@dma.isg.mot.com

   Andrew Smith (editor)
   Harbour Networks
   Jiuling Building
   21 North Xisanhuan Ave.
   Beijing, 100089
   PRC

   Fax: +1 415 345 1827
   EMail: ah_smith@acm.org



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Full Copyright Statement

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Bernet, et. al.              Informational                     [Page 56]
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