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RFC 3272

Overview and Principles of Internet Traffic Engineering

Pages: 71
Informational
Errata
Updated by:  5462
Part 1 of 3 – Pages 1 to 21
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Network Working Group                                         D. Awduche
Request for Comments: 3272                                Movaz Networks
Category: Informational                                          A. Chiu
                                                         Celion Networks
                                                              A. Elwalid
                                                              I. Widjaja
                                                     Lucent Technologies
                                                                 X. Xiao
                                                        Redback Networks
                                                                May 2002


        Overview and Principles of Internet Traffic Engineering

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 memo describes the principles of Traffic Engineering (TE) in the Internet. The document is intended to promote better understanding of the issues surrounding traffic engineering in IP networks, and to provide a common basis for the development of traffic engineering capabilities for the Internet. The principles, architectures, and methodologies for performance evaluation and performance optimization of operational IP networks are discussed throughout this document.

Table of Contents

1.0 Introduction...................................................3 1.1 What is Internet Traffic Engineering?.......................4 1.2 Scope.......................................................7 1.3 Terminology.................................................8 2.0 Background....................................................11 2.1 Context of Internet Traffic Engineering....................12 2.2 Network Context............................................13 2.3 Problem Context............................................14 2.3.1 Congestion and its Ramifications......................16 2.4 Solution Context...........................................16 2.4.1 Combating the Congestion Problem......................18 2.5 Implementation and Operational Context.....................21
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   3.0 Traffic Engineering Process Model.............................21
      3.1 Components of the Traffic Engineering Process Model........23
      3.2 Measurement................................................23
      3.3 Modeling, Analysis, and Simulation.........................24
      3.4 Optimization...............................................25
   4.0 Historical Review and Recent Developments.....................26
      4.1 Traffic Engineering in Classical Telephone Networks........26
      4.2 Evolution of Traffic Engineering in the Internet...........28
         4.2.1 Adaptive Routing in ARPANET...........................28
         4.2.2 Dynamic Routing in the Internet.......................29
         4.2.3 ToS Routing...........................................30
         4.2.4 Equal Cost Multi-Path.................................30
         4.2.5 Nimrod................................................31
      4.3 Overlay Model..............................................31
      4.4 Constraint-Based Routing...................................32
      4.5 Overview of Other IETF Projects Related to Traffic
          Engineering................................................32
         4.5.1 Integrated Services...................................32
         4.5.2 RSVP..................................................33
         4.5.3 Differentiated Services...............................34
         4.5.4 MPLS..................................................35
         4.5.5 IP Performance Metrics................................36
         4.5.6 Flow Measurement......................................37
         4.5.7 Endpoint Congestion Management........................37
      4.6 Overview of ITU Activities Related to Traffic
          Engineering................................................38
      4.7 Content Distribution.......................................39
   5.0 Taxonomy of Traffic Engineering Systems.......................40
      5.1 Time-Dependent Versus State-Dependent......................40
      5.2 Offline Versus Online......................................41
      5.3 Centralized Versus Distributed.............................42
      5.4 Local Versus Global........................................42
      5.5 Prescriptive Versus Descriptive............................42
      5.6 Open-Loop Versus Closed-Loop...............................43
      5.7 Tactical vs Strategic......................................43
   6.0 Recommendations for Internet Traffic Engineering..............43
      6.1 Generic Non-functional Recommendations.....................44
      6.2 Routing Recommendations....................................46
      6.3 Traffic Mapping Recommendations............................48
      6.4 Measurement Recommendations................................49
      6.5 Network Survivability......................................50
         6.5.1 Survivability in MPLS Based Networks..................52
         6.5.2 Protection Option.....................................53
      6.6 Traffic Engineering in Diffserv Environments...............54
      6.7 Network Controllability....................................56
   7.0 Inter-Domain Considerations...................................57
   8.0 Overview of Contemporary TE Practices in Operational
       IP Networks...................................................59
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   9.0 Conclusion....................................................63
   10.0 Security Considerations......................................63
   11.0 Acknowledgments..............................................63
   12.0 References...................................................64
   13.0 Authors' Addresses...........................................70
   14.0 Full Copyright Statement.....................................71

1.0 Introduction

This memo describes the principles of Internet traffic engineering. The objective of the document is to articulate the general issues and principles for Internet traffic engineering; and where appropriate to provide recommendations, guidelines, and options for the development of online and offline Internet traffic engineering capabilities and support systems. This document can aid service providers in devising and implementing traffic engineering solutions for their networks. Networking hardware and software vendors will also find this document helpful in the development of mechanisms and support systems for the Internet environment that support the traffic engineering function. This document provides a terminology for describing and understanding common Internet traffic engineering concepts. This document also provides a taxonomy of known traffic engineering styles. In this context, a traffic engineering style abstracts important aspects from a traffic engineering methodology. Traffic engineering styles can be viewed in different ways depending upon the specific context in which they are used and the specific purpose which they serve. The combination of styles and views results in a natural taxonomy of traffic engineering systems. Even though Internet traffic engineering is most effective when applied end-to-end, the initial focus of this document document is intra-domain traffic engineering (that is, traffic engineering within a given autonomous system). However, because a preponderance of Internet traffic tends to be inter-domain (originating in one autonomous system and terminating in another), this document provides an overview of aspects pertaining to inter-domain traffic engineering. The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT", "SHOULD", "SHOULD NOT", "RECOMMENDED", "MAY", and "OPTIONAL" in this document are to be interpreted as described in RFC 2119.
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1.1. What is Internet Traffic Engineering?

Internet traffic engineering is defined as that aspect of Internet network engineering dealing with the issue of performance evaluation and performance optimization of operational IP networks. Traffic Engineering encompasses the application of technology and scientific principles to the measurement, characterization, modeling, and control of Internet traffic [RFC-2702, AWD2]. Enhancing the performance of an operational network, at both the traffic and resource levels, are major objectives of Internet traffic engineering. This is accomplished by addressing traffic oriented performance requirements, while utilizing network resources economically and reliably. Traffic oriented performance measures include delay, delay variation, packet loss, and throughput. An important objective of Internet traffic engineering is to facilitate reliable network operations [RFC-2702]. Reliable network operations can be facilitated by providing mechanisms that enhance network integrity and by embracing policies emphasizing network survivability. This results in a minimization of the vulnerability of the network to service outages arising from errors, faults, and failures occurring within the infrastructure. The Internet exists in order to transfer information from source nodes to destination nodes. Accordingly, one of the most significant functions performed by the Internet is the routing of traffic from ingress nodes to egress nodes. Therefore, one of the most distinctive functions performed by Internet traffic engineering is the control and optimization of the routing function, to steer traffic through the network in the most effective way. Ultimately, it is the performance of the network as seen by end users of network services that is truly paramount. This crucial point should be considered throughout the development of traffic engineering mechanisms and policies. The characteristics visible to end users are the emergent properties of the network, which are the characteristics of the network when viewed as a whole. A central goal of the service provider, therefore, is to enhance the emergent properties of the network while taking economic considerations into account. The importance of the above observation regarding the emergent properties of networks is that special care must be taken when choosing network performance measures to optimize. Optimizing the wrong measures may achieve certain local objectives, but may have
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   disastrous consequences on the emergent properties of the network and
   thereby on the quality of service perceived by end-users of network
   services.

   A subtle, but practical advantage of the systematic application of
   traffic engineering concepts to operational networks is that it helps
   to identify and structure goals and priorities in terms of enhancing
   the quality of service delivered to end-users of network services.
   The application of traffic engineering concepts also aids in the
   measurement and analysis of the achievement of these goals.

   The optimization aspects of traffic engineering can be achieved
   through capacity management and traffic management.  As used in this
   document, capacity management includes capacity planning, routing
   control, and resource management.  Network resources of particular
   interest include link bandwidth, buffer space, and computational
   resources.  Likewise, as used in this document, traffic management
   includes (1) nodal traffic control functions such as traffic
   conditioning, queue management, scheduling, and (2) other functions
   that regulate traffic flow through the network or that arbitrate
   access to network resources between different packets or between
   different traffic streams.

   The optimization objectives of Internet traffic engineering should be
   viewed as a continual and iterative process of network performance
   improvement and not simply as a one time goal.  Traffic engineering
   also demands continual development of new technologies and new
   methodologies for network performance enhancement.

   The optimization objectives of Internet traffic engineering may
   change over time as new requirements are imposed, as new technologies
   emerge, or as new insights are brought to bear on the underlying
   problems.  Moreover, different networks may have different
   optimization objectives, depending upon their business models,
   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.

      - Provisioning:
            The process of assigning or configuring network resources to
            meet certain requests.

      - QoS routing:
            Class of routing systems that selects paths to be used by a
            flow based on the QoS requirements of the flow.

      - Service Level Agreement:
            A contract between a provider and a customer that guarantees
            specific levels of performance and reliability at a certain
            cost.

      - Stability:
            An operational state in which a network does not oscillate
            in a disruptive manner from one mode to another mode.

      - Supply side congestion management:
            A congestion management scheme that provisions additional
            network resources to address existing and/or anticipated
            congestion problems.

      - Transit traffic:
            Traffic whose origin and destination are both outside of the
            network under consideration.

      - Traffic characteristic:
            A description of the temporal behavior or a description of
            the attributes of a given traffic flow or traffic aggregate.
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      - Traffic engineering system:
            A collection of objects, mechanisms, and protocols that are
            used conjunctively to accomplish traffic engineering
            objectives.

      - Traffic flow:
            A stream of packets between two end-points that can be
            characterized in a certain way.  A micro-flow has a more
            specific definition: A micro-flow is a stream of packets
            with the same source and destination addresses, source and
            destination ports, and protocol ID.

      - Traffic intensity:
            A measure of traffic loading with respect to a resource
            capacity over a specified period of time.  In classical
            telephony systems, traffic intensity is measured in units of
            Erlang.

      - Traffic matrix:
            A representation of the traffic demand between a set of
            origin and destination abstract nodes.  An abstract node can
            consist of one or more network elements.

      - Traffic monitoring:
            The process of observing traffic characteristics at a given
            point in a network and collecting the traffic information
            for analysis and further action.

      - Traffic trunk:
            An aggregation of traffic flows belonging to the same class
            which are forwarded through a common path.  A traffic trunk
            may be characterized by an ingress and egress node, and a
            set of attributes which determine its behavioral
            characteristics and requirements from the network.

2.0 Background

The Internet has quickly evolved into a very critical communications infrastructure, supporting significant economic, educational, and social activities. Simultaneously, the delivery of Internet communications services has become very competitive and end-users are demanding very high quality service from their service providers. Consequently, performance optimization of large scale IP networks, especially public Internet backbones, have become an important problem. Network performance requirements are multi-dimensional, complex, and sometimes contradictory; making the traffic engineering problem very challenging.
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   The network must convey IP packets from ingress nodes to egress nodes
   efficiently, expeditiously, and economically.  Furthermore, in a
   multiclass service environment (e.g., Diffserv capable networks), the
   resource sharing parameters of the network must be appropriately
   determined and configured according to prevailing policies and
   service models to resolve resource contention issues arising from
   mutual interference between packets traversing through the network.
   Thus, consideration must be given to resolving competition for
   network resources between traffic streams belonging to the same
   service class (intra-class contention resolution) and traffic streams
   belonging to different classes (inter-class contention resolution).

2.1 Context of Internet Traffic Engineering

The context of Internet traffic engineering pertains to the scenarios where traffic engineering is used. A traffic engineering methodology establishes appropriate rules to resolve traffic performance issues occurring in a specific context. The context of Internet traffic engineering includes: (1) A network context defining the universe of discourse, and in particular the situations in which the traffic engineering problems occur. The network context includes network structure, network policies, network characteristics, network constraints, network quality attributes, and network optimization criteria. (2) A problem context defining the general and concrete issues that traffic engineering addresses. The problem context includes identification, abstraction of relevant features, representation, formulation, specification of the requirements on the solution space, and specification of the desirable features of acceptable solutions. (3) A solution context suggesting how to address the issues identified by the problem context. The solution context includes analysis, evaluation of alternatives, prescription, and resolution. (4) An implementation and operational context in which the solutions are methodologically instantiated. The implementation and operational context includes planning, organization, and execution. The context of Internet traffic engineering and the different problem scenarios are discussed in the following subsections.
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2.2 Network Context

IP networks range in size from small clusters of routers situated within a given location, to thousands of interconnected routers, switches, and other components distributed all over the world. Conceptually, at the most basic level of abstraction, an IP network can be represented as a distributed dynamical system consisting of: (1) a set of interconnected resources which provide transport services for IP traffic subject to certain constraints, (2) a demand system representing the offered load to be transported through the network, and (3) a response system consisting of network processes, protocols, and related mechanisms which facilitate the movement of traffic through the network [see also AWD2]. The network elements and resources may have specific characteristics restricting the manner in which the demand is handled. Additionally, network resources may be equipped with traffic control mechanisms superintending the way in which the demand is serviced. Traffic control mechanisms may, for example, be used to control various packet processing activities within a given resource, arbitrate contention for access to the resource by different packets, and regulate traffic behavior through the resource. A configuration management and provisioning system may allow the settings of the traffic control mechanisms to be manipulated by external or internal entities in order to exercise control over the way in which the network elements respond to internal and external stimuli. The details of how the network provides transport services for packets are specified in the policies of the network administrators and are installed through network configuration management and policy based provisioning systems. Generally, the types of services provided by the network also depends upon the technology and characteristics of the network elements and protocols, the prevailing service and utility models, and the ability of the network administrators to translate policies into network configurations. Contemporary Internet networks have three significant characteristics: (1) they provide real-time services, (2) they have become mission critical, and (3) their operating environments are very dynamic. The dynamic characteristics of IP networks can be attributed in part to fluctuations in demand, to the interaction between various network protocols and processes, to the rapid evolution of the infrastructure which demands the constant inclusion of new technologies and new network elements, and to transient and persistent impairments which occur within the system.
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   Packets contend for the use of network resources as they are conveyed
   through the network.  A network resource is considered to be
   congested if the arrival rate of packets exceed the output capacity
   of the resource over an interval of time.  Congestion may result in
   some of the arrival packets being delayed or even dropped.

   Congestion increases transit delays, delay variation, packet loss,
   and reduces the predictability of network services.  Clearly,
   congestion is a highly undesirable phenomenon.

   Combating congestion at a reasonable cost is a major objective of
   Internet traffic engineering.

   Efficient sharing of network resources by multiple traffic streams is
   a basic economic premise for packet switched networks in general and
   for the Internet in particular.  A fundamental challenge in network
   operation, especially in a large scale public IP network, is to
   increase the efficiency of resource utilization while minimizing the
   possibility of congestion.

   Increasingly, the Internet will have to function in the presence of
   different classes of traffic with different service requirements.
   The advent of Differentiated Services [RFC-2475] makes this
   requirement particularly acute.  Thus, packets may be grouped into
   behavior aggregates such that each behavior aggregate may have a
   common set of behavioral characteristics or a common set of delivery
   requirements.  In practice, the delivery requirements of a specific
   set of packets may be specified explicitly or implicitly.  Two of the
   most important traffic delivery requirements are capacity constraints
   and QoS constraints.

   Capacity constraints can be expressed statistically as peak rates,
   mean rates, burst sizes, or as some deterministic notion of effective
   bandwidth.  QoS requirements can be expressed in terms of (1)
   integrity constraints such as packet loss and (2) in terms of
   temporal constraints such as timing restrictions for the delivery of
   each packet (delay) and timing restrictions for the delivery of
   consecutive packets belonging to the same traffic stream (delay
   variation).

2.3 Problem Context

Fundamental problems exist in association with the operation of a network described by the simple model of the previous subsection. This subsection reviews the problem context in relation to the traffic engineering function.
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   The identification, abstraction, representation, and measurement of
   network features relevant to traffic engineering is a significant
   issue.

   One particularly important class of problems concerns how to
   explicitly formulate the problems that traffic engineering attempts
   to solve, how to identify the requirements on the solution space, how
   to specify the desirable features of good solutions, how to actually
   solve the problems, and how to measure and characterize the
   effectiveness of the solutions.

   Another class of problems concerns how to measure and estimate
   relevant network state parameters.  Effective traffic engineering
   relies on a good estimate of the offered traffic load as well as a
   view of the underlying topology and associated resource constraints.
   A network-wide view of the topology is also a must for offline
   planning.

   Still another class of problems concerns how to characterize the
   state of the network and how to evaluate its performance under a
   variety of scenarios.  The performance evaluation problem is two-
   fold.  One aspect of this problem relates to the evaluation of the
   system level performance of the network.  The other aspect relates to
   the evaluation of the resource level performance, which restricts
   attention to the performance analysis of individual network
   resources.  In this memo, we refer to the system level
   characteristics of the network as the "macro-states" and the resource
   level characteristics as the "micro-states." The system level
   characteristics are also known as the emergent properties of the
   network as noted earlier.  Correspondingly, we shall refer to the
   traffic engineering schemes dealing with network performance
   optimization at the systems level as "macro-TE" and the schemes that
   optimize at the individual resource level as "micro-TE."  Under
   certain circumstances, the system level performance can be derived
   from the resource level performance using appropriate rules of
   composition, depending upon the particular performance measures of
   interest.

   Another fundamental class of problems concerns how to effectively
   optimize network performance.  Performance optimization may entail
   translating solutions to specific traffic engineering problems into
   network configurations.  Optimization may also entail some degree of
   resource management control, routing control, and/or capacity
   augmentation.
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   As noted previously, congestion is an undesirable phenomena in
   operational networks.  Therefore, the next subsection addresses the
   issue of congestion and its ramifications within the problem context
   of Internet traffic engineering.

2.3.1 Congestion and its Ramifications

Congestion is one of the most significant problems in an operational IP context. A network element is said to be congested if it experiences sustained overload over an interval of time. Congestion almost always results in degradation of service quality to end users. Congestion control schemes can include demand side policies and supply side policies. Demand side policies may restrict access to congested resources and/or dynamically regulate the demand to alleviate the overload situation. Supply side policies may expand or augment network capacity to better accommodate offered traffic. Supply side policies may also re-allocate network resources by redistributing traffic over the infrastructure. Traffic redistribution and resource re-allocation serve to increase the 'effective capacity' seen by the demand. The emphasis of this memo is primarily on congestion management schemes falling within the scope of the network, rather than on congestion management systems dependent upon sensitivity and adaptivity from end-systems. That is, the aspects that are considered in this memo with respect to congestion management are those solutions that can be provided by control entities operating on the network and by the actions of network administrators and network operations systems.

2.4 Solution Context

The solution context for Internet traffic engineering involves analysis, evaluation of alternatives, and choice between alternative courses of action. Generally the solution context is predicated on making reasonable inferences about the current or future state of the network, and subsequently making appropriate decisions that may involve a preference between alternative sets of action. More specifically, the solution context demands reasonable estimates of traffic workload, characterization of network state, deriving solutions to traffic engineering problems which may be implicitly or explicitly formulated, and possibly instantiating a set of control actions. Control actions may involve the manipulation of parameters associated with routing, control over tactical capacity acquisition, and control over the traffic management functions. The following list of instruments may be applicable to the solution context of Internet traffic engineering.
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      (1)   A set of policies, objectives, and requirements (which may
            be context dependent) for network performance evaluation and
            performance  optimization.

      (2)   A collection of online and possibly offline tools and
            mechanisms for measurement, characterization, modeling, and
            control of Internet traffic and control over the placement
            and allocation of network resources, as well as control over
            the mapping or distribution of traffic onto the
            infrastructure.

      (3)   A set of constraints on the operating environment, the
            network protocols, and the traffic engineering system
            itself.

      (4)   A set of quantitative and qualitative techniques and
            methodologies for abstracting, formulating, and solving
            traffic engineering problems.

      (5)   A set of administrative control parameters which may be
            manipulated through a Configuration Management (CM) system.
            The CM system itself may include a configuration control
            subsystem, a configuration repository, a configuration
            accounting subsystem, and a configuration auditing
            subsystem.

      (6)   A set of guidelines for network performance evaluation,
            performance optimization, and performance improvement.

   Derivation of traffic characteristics through measurement and/or
   estimation is very useful within the realm of the solution space for
   traffic engineering.  Traffic estimates can be derived from customer
   subscription information, traffic projections, traffic models, and
   from actual empirical measurements.  The empirical measurements may
   be performed at the traffic aggregate level or at the flow level in
   order to derive traffic statistics at various levels of detail.
   Measurements at the flow level or on small traffic aggregates may be
   performed at edge nodes, where traffic enters and leaves the network.
   Measurements at large traffic aggregate levels may be performed
   within the core of the network where potentially numerous traffic
   flows may be in transit concurrently.

   To conduct performance studies and to support planning of existing
   and future networks, a routing analysis may be performed to determine
   the path(s) the routing protocols will choose for various traffic
   demands, and to ascertain the utilization of network resources as
   traffic is routed through the network.  The routing analysis should
   capture the selection of paths through the network, the assignment of
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   traffic across multiple feasible routes, and the multiplexing of IP
   traffic over traffic trunks (if such constructs exists) and over the
   underlying network infrastructure.  A network topology model is a
   necessity for routing analysis.  A network topology model may be
   extracted from network architecture documents, from network designs,
   from information contained in router configuration files, from
   routing databases, from routing tables, or from automated tools that
   discover and depict network topology information.  Topology
   information may also be derived from servers that monitor network
   state, and from servers that perform provisioning functions.

   Routing in operational IP networks can be administratively controlled
   at various levels of abstraction including the manipulation of BGP
   attributes and manipulation of IGP metrics.  For path oriented
   technologies such as MPLS, routing can be further controlled by the
   manipulation of relevant traffic engineering parameters, resource
   parameters, and administrative policy constraints.  Within the
   context of MPLS, the path of an explicit label switched path (LSP)
   can be computed and established in various ways including: (1)
   manually, (2) automatically online using constraint-based routing
   processes implemented on label switching routers, and (3)
   automatically offline using constraint-based routing entities
   implemented on external traffic engineering support systems.

2.4.1 Combating the Congestion Problem

Minimizing congestion is a significant aspect of Internet traffic engineering. This subsection gives an overview of the general approaches that have been used or proposed to combat congestion problems. Congestion management policies can be categorized based upon the following criteria (see e.g., [YARE95] for a more detailed taxonomy of congestion control schemes): (1) Response time scale which can be characterized as long, medium, or short; (2) reactive versus preventive which relates to congestion control and congestion avoidance; and (3) supply side versus demand side congestion management schemes. These aspects are discussed in the following paragraphs. (1) Congestion Management based on Response Time Scales - Long (weeks to months): Capacity planning works over a relatively long time scale to expand network capacity based on estimates or forecasts of future traffic demand and traffic distribution. Since router and link provisioning take time and are generally expensive, these upgrades are typically carried out in the weeks-to-months or even years time scale.
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   - Medium (minutes to days): Several control policies fall within the
   medium time scale category.  Examples include: (1) Adjusting IGP
   and/or BGP parameters to route traffic away or towards certain
   segments of the network; (2) Setting up and/or adjusting some
   explicitly routed label switched paths (ER-LSPs) in MPLS networks to
   route some traffic trunks away from possibly congested resources or
   towards possibly more favorable routes; (3) re-configuring the
   logical topology of the network to make it correlate more closely
   with the spatial traffic distribution using for example some
   underlying path-oriented technology such as MPLS LSPs, ATM PVCs, or
   optical channel trails.  Many of these adaptive medium time scale
   response schemes rely on a measurement system that monitors changes
   in traffic distribution, traffic shifts, and network resource
   utilization and subsequently provides feedback to the online and/or
   offline traffic engineering mechanisms and tools which employ this
   feedback information to trigger certain control actions to occur
   within the network.  The traffic engineering mechanisms and tools can
   be implemented in a distributed fashion or in a centralized fashion,
   and may have a hierarchical structure or a flat structure.  The
   comparative merits of distributed and centralized control structures
   for networks are well known.  A centralized scheme may have global
   visibility into the network state and may produce potentially more
   optimal solutions.  However, centralized schemes are prone to single
   points of failure and may not scale as well as distributed schemes.
   Moreover, the information utilized by a centralized scheme may be
   stale and may not reflect the actual state of the network.  It is not
   an objective of this memo to make a recommendation between
   distributed and centralized schemes.  This is a choice that network
   administrators must make based on their specific needs.

   - Short (picoseconds to minutes): This category includes packet level
   processing functions and events on the order of several round trip
   times.  It includes router mechanisms such as passive and active
   buffer management.  These mechanisms are used to control congestion
   and/or signal congestion to end systems so that they can adaptively
   regulate the rate at which traffic is injected into the network.  One
   of the most popular active queue management schemes, especially for
   TCP traffic, is Random Early Detection (RED) [FLJA93], which supports
   congestion avoidance by controlling the average queue size.  During
   congestion (but before the queue is filled), the RED scheme chooses
   arriving packets to "mark" according to a probabilistic algorithm
   which takes into account the average queue size.  For a router that
   does not utilize explicit congestion notification (ECN) see e.g.,
   [FLOY94], the marked packets can simply be dropped to signal the
   inception of congestion to end systems.  On the other hand, if the
   router supports ECN, then it can set the ECN field in the packet
   header.  Several variations of RED have been proposed to support
   different drop precedence levels in multi-class environments [RFC-
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   2597], e.g., RED with In and Out (RIO) and Weighted RED.  There is
   general consensus that RED provides congestion avoidance performance
   which is not worse than traditional Tail-Drop (TD) queue management
   (drop arriving packets only when the queue is full).  Importantly,
   however, RED reduces the possibility of global synchronization and
   improves fairness among different TCP sessions.  However, RED by
   itself can not prevent congestion and unfairness caused by sources
   unresponsive to RED, e.g., UDP traffic and some misbehaved greedy
   connections.  Other schemes have been proposed to improve the
   performance and fairness in the presence of unresponsive traffic.
   Some of these schemes were proposed as theoretical frameworks and are
   typically not available in existing commercial products.  Two such
   schemes are Longest Queue Drop (LQD) and Dynamic Soft Partitioning
   with Random Drop (RND) [SLDC98].

   (2) Congestion Management: Reactive versus Preventive Schemes

   - Reactive: reactive (recovery) congestion management policies react
   to existing congestion problems to improve it.  All the policies
   described in the long and medium time scales above can be categorized
   as being reactive especially if the policies are based on monitoring
   and identifying existing congestion problems, and on the initiation
   of relevant actions to ease a situation.

   - Preventive: preventive (predictive/avoidance) policies take
   proactive action to prevent congestion based on estimates and
   predictions of future potential congestion problems.  Some of the
   policies described in the long and medium time scales fall into this
   category.  They do not necessarily respond immediately to existing
   congestion problems.  Instead forecasts of traffic demand and
   workload distribution are considered and action may be taken to
   prevent potential congestion problems in the future.  The schemes
   described in the short time scale (e.g., RED and its variations, ECN,
   LQD, and RND) are also used for congestion avoidance since dropping
   or marking packets before queues actually overflow would trigger
   corresponding TCP sources to slow down.

   (3) Congestion Management: Supply Side versus Demand Side Schemes

   - Supply side: supply side congestion management policies increase
   the effective capacity available to traffic in order to control or
   obviate congestion.  This can be accomplished by augmenting capacity.
   Another way to accomplish this is to minimize congestion by having a
   relatively balanced distribution of traffic over the network.  For
   example, capacity planning should aim to provide a physical topology
   and associated link bandwidths that match estimated traffic workload
   and traffic distribution based on forecasting (subject to budgetary
   and other constraints).  However, if actual traffic distribution does
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   not match the topology derived from capacity panning (due to
   forecasting errors or facility constraints for example), then the
   traffic can be mapped onto the existing topology using routing
   control mechanisms, using path oriented technologies (e.g., MPLS LSPs
   and optical channel trails) to modify the logical topology, or by
   using some other load redistribution mechanisms.

   - Demand side: demand side congestion management policies control or
   regulate the offered traffic to alleviate congestion problems.  For
   example, some of the short time scale mechanisms described earlier
   (such as RED and its variations, ECN, LQD, and RND) as well as
   policing and rate shaping mechanisms attempt to regulate the offered
   load in various ways.  Tariffs may also be applied as a demand side
   instrument.  To date, however, tariffs have not been used as a means
   of demand side congestion management within the Internet.

   In summary, a variety of mechanisms can be used to address congestion
   problems in IP networks.  These mechanisms may operate at multiple
   time-scales.

2.5 Implementation and Operational Context

The operational context of Internet traffic engineering is characterized by constant change which occur at multiple levels of abstraction. The implementation context demands effective planning, organization, and execution. The planning aspects may involve determining prior sets of actions to achieve desired objectives. Organizing involves arranging and assigning responsibility to the various components of the traffic engineering system and coordinating the activities to accomplish the desired TE objectives. Execution involves measuring and applying corrective or perfective actions to attain and maintain desired TE goals.


(page 21 continued on part 2)

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