rfc3272.txt

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   capabilities, and operating constraints.  The optimization aspects of
   traffic engineering are ultimately concerned with network control
   regardless of the specific optimization goals in any particular
   environment.

   Thus, the optimization aspects of traffic engineering can be viewed
   from a control perspective.  The aspect of control within the
   Internet traffic engineering arena can be pro-active and/or reactive.
   In the pro-active case, the traffic engineering control system takes
   preventive action to obviate predicted unfavorable future network
   states.  It may also take perfective action to induce a more
   desirable state in the future.  In the reactive case, the control
   system responds correctively and perhaps adaptively to events that
   have already transpired in the network.



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   The control dimension of Internet traffic engineering responds at
   multiple levels of temporal resolution to network events.  Certain
   aspects of capacity management, such as capacity planning, respond at
   very coarse temporal levels, ranging from days to possibly years.
   The introduction of automatically switched optical transport networks
   (e.g., based on the Multi-protocol Lambda Switching concepts) could
   significantly reduce the lifecycle for capacity planning by
   expediting provisioning of optical bandwidth.  Routing control
   functions operate at intermediate levels of temporal resolution,
   ranging from milliseconds to days.  Finally, the packet level
   processing functions (e.g., rate shaping, queue management, and
   scheduling) operate at very fine levels of temporal resolution,
   ranging from picoseconds to milliseconds while responding to the
   real-time statistical behavior of traffic.  The subsystems of
   Internet traffic engineering control include: capacity augmentation,
   routing control, traffic control, and resource control (including
   control of service policies at network elements).  When capacity is
   to be augmented for tactical purposes, it may be desirable to devise
   a deployment plan that expedites bandwidth provisioning while
   minimizing installation costs.

   Inputs into the traffic engineering control system include network
   state variables, policy variables, and decision variables.

   One major challenge of Internet traffic engineering is the
   realization of automated control capabilities that adapt quickly and
   cost effectively to significant changes in a network's state, while
   still maintaining stability.

   Another critical dimension of Internet traffic engineering is network
   performance evaluation, which is important for assessing the
   effectiveness of traffic engineering methods, and for monitoring and
   verifying compliance with network performance goals.  Results from
   performance evaluation can be used to identify existing problems,
   guide network re-optimization, and aid in the prediction of potential
   future problems.

   Performance evaluation can be achieved in many different ways.  The
   most notable techniques include analytical methods, simulation, and
   empirical methods based on measurements.  When analytical methods or
   simulation are used, network nodes and links can be modeled to
   capture relevant operational features such as topology, bandwidth,
   buffer space, and nodal service policies (link scheduling, packet
   prioritization, buffer management, etc.).  Analytical traffic models
   can be used to depict dynamic and behavioral traffic characteristics,
   such as burstiness, statistical distributions, and dependence.





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   Performance evaluation can be quite complicated in practical network
   contexts.  A number of techniques can be used to simplify the
   analysis, such as abstraction, decomposition, and approximation.  For
   example, simplifying concepts such as effective bandwidth and
   effective buffer [Elwalid] may be used to approximate nodal behaviors
   at the packet level and simplify the analysis at the connection
   level.  Network analysis techniques using, for example, queuing
   models and approximation schemes based on asymptotic and
   decomposition techniques can render the analysis even more tractable.
   In particular, an emerging set of concepts known as network calculus
   [CRUZ] based on deterministic bounds may simplify network analysis
   relative to classical stochastic techniques.  When using analytical
   techniques, care should be taken to ensure that the models faithfully
   reflect the relevant operational characteristics of the modeled
   network entities.

   Simulation can be used to evaluate network performance or to verify
   and validate analytical approximations.  Simulation can, however, be
   computationally costly and may not always provide sufficient
   insights.  An appropriate approach to a given network performance
   evaluation problem may involve a hybrid combination of analytical
   techniques, simulation, and empirical methods.

   As a general rule, traffic engineering concepts and mechanisms must
   be sufficiently specific and well defined to address known
   requirements, but simultaneously flexible and extensible to
   accommodate unforeseen future demands.

1.2. Scope

   The scope of this document is intra-domain traffic engineering; that
   is, traffic engineering within a given autonomous system in the
   Internet.  This document will discuss concepts pertaining to intra-
   domain traffic control, including such issues as routing control,
   micro and macro resource allocation, and the control coordination
   problems that arise consequently.

   This document will describe and characterize techniques already in
   use or in advanced development for Internet traffic engineering.  The
   way these techniques fit together will be discussed and scenarios in
   which they are useful will be identified.

   While this document considers various intra-domain traffic
   engineering approaches, it focuses more on traffic engineering with
   MPLS.  Traffic engineering based upon manipulation of IGP metrics is
   not addressed in detail.  This topic may be addressed by other
   working group document(s).




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   Although the emphasis is on intra-domain traffic engineering, in
   Section 7.0, an overview of the high level considerations pertaining
   to inter-domain traffic engineering will be provided.  Inter-domain
   Internet traffic engineering is crucial to the performance
   enhancement of the global Internet infrastructure.

   Whenever possible, relevant requirements from existing IETF documents
   and other sources will be incorporated by reference.

1.3 Terminology

   This subsection provides terminology which is useful for Internet
   traffic engineering.  The definitions presented apply to this
   document.  These terms may have other meanings elsewhere.

      - Baseline analysis:
            A study conducted to serve as a baseline for comparison to
            the actual behavior of the network.

      - Busy hour:
            A one hour period within a specified interval of time
            (typically 24 hours) in which the traffic load in a network
            or sub-network is greatest.

      - Bottleneck:
            A network element whose input traffic rate tends to be
            greater than its output rate.

      - Congestion:
            A state of a network resource in which the traffic incident
            on the resource exceeds its output capacity over an interval
            of time.

      - Congestion avoidance:
            An approach to congestion management that attempts to
            obviate the occurrence of congestion.

      - Congestion control:
            An approach to congestion management that attempts to remedy
            congestion problems that have already occurred.

      - Constraint-based routing:
            A class of routing protocols that take specified traffic
            attributes, network constraints, and policy constraints into
            account when making routing decisions.  Constraint-based
            routing is applicable to traffic aggregates as well as
            flows.  It is a generalization of QoS routing.




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      - Demand side congestion management:
            A congestion management scheme that addresses congestion
            problems by regulating or conditioning offered load.

      - Effective bandwidth:
            The minimum amount of bandwidth that can be assigned to a
            flow or traffic aggregate in order to deliver 'acceptable
            service quality' to the flow or traffic aggregate.

      - Egress traffic:
            Traffic exiting a network or network element.

      - Hot-spot:
            A network element or subsystem which is in a state of
            congestion.

      - Ingress traffic:
            Traffic entering a network or network element.

      - Inter-domain traffic:
            Traffic that originates in one Autonomous system and
            terminates in another.

      - Loss network:
            A network that does not provide adequate buffering for
            traffic, so that traffic entering a busy resource within the
            network will be dropped rather than queued.

      - Metric:
            A parameter defined in terms of standard units of
            measurement.

      - Measurement Methodology:
            A repeatable measurement technique used to derive one or
            more metrics of interest.

      - Network Survivability:
            The capability to provide a prescribed level of QoS for
            existing services after a given number of failures occur
            within the network.

      - Offline traffic engineering:
            A traffic engineering system that exists outside of the
            network.







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      - Online traffic engineering:
            A traffic engineering system that exists within the network,
            typically implemented on or as adjuncts to operational
            network elements.

      - Performance measures:
            Metrics that provide quantitative or qualitative measures of
            the performance of systems or subsystems of interest.

      - Performance management:
            A systematic approach to improving effectiveness in the
            accomplishment of specific networking goals related to
            performance improvement.

      - Performance Metric:
            A performance parameter defined in terms of standard units
            of measurement.