Internet Draft

Traffic Engineering Working Group                              W.S. Lai
Internet Draft                                                AT&T Labs
Document: <draft-wlai-tewg-cap-eng-01.txt>                    July 2000
Expiration Date: January 2001


          Capacity Engineering of IP-Based Networks with MPLS


Status of this Memo

   This document is an Internet-Draft and is in full conformance with
   all provisions of Section 10 of RFC2026.

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Abstract

   Drawing from the experience and work done in ITU-T on traffic
   engineering, the feasibility of extending telecommunications network
   dimensioning methods to IP-based networks with MPLS is explored.
   This version of the document is preliminary, reporting work in
   progress.


1. Introduction

   The routing protocols currently used in public IP networks are
   typically traffic-insensitive in that they do not include network
   resource utilization information in making routing decisions.  As a
   result of this lack of traffic control, traffic tends to converge
   onto the same network segments, thereby causing unbalanced network
   loading with subsets of network resources at the "hot spots" being
   congested and other resources being underutilized.  This shortcoming
   of network operation, coupled with the phenomenal growth of Internet
   usage, makes it very difficult to manage IP-based network
   performance.  Hence, current engineering practice sometimes resorts
   to over-provisioning of network capacity.

   As IP-based network services evolve from a single best-effort class
   toward differentiation with multiple levels of quality of service

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   (QoS), a network infrastructure that offers consistent and
   predictable network performance is required.  To achieve this,
   proper control and provisioning of network resources would be
   needed.  Recently, it has been proposed that the multiprotocol label
   switching (MPLS) technology [1, 2] be used to overcome the above
   limitations of existing destination-based routing protocols so that
   more effective traffic engineering of IP-based networks can be
   performed.

   Such use of MPLS is discussed in the next section.  To take full
   advantage of the mechanisms offered by MPLS, engineering and
   networking principles for resource management must be established,
   especially in the support for QoS [3].  This is the subject that is
   addressed here, with focus on the dimensioning aspect of traffic
   engineering and its related tasks.  Topics covered include general
   aspects of traffic engineering, capacity engineering, traffic demand
   characterization, performance objectives and reference connections,
   and network dimensioning.  Much of the materials presented here are
   adapted and drawn from the experience and work done in ITU-T on
   traffic engineering of telecommunications networks.

2. The Utility of MPLS

   Built upon the notion of separating packet forwarding and routing
   control functions [4], MPLS uses the technique of swapping link
   local labels to forward packets [5].  Originally, this technique was
   developed as a way of fast switching, so-called "short-cut routing,"
   to simplify the packet processing tasks within a conventional IP
   router in a core network.  With the advent of hardware-intensive
   high-speed routers, it now appears that the performance of
   destination-based network-layer forwarding in an IP router may be
   comparable to that of MPLS in a label-switching router (LSR).
   Currently, a major driver of MPLS is its application to traffic
   engineering.

   MPLS integrates the connection-oriented label-swapping operation
   with the connectionless network-layer routing/forwarding functions,
   thus gaining much of the control capabilities of a connection-
   oriented network such as ATM-based B-ISDN.  In particular, MPLS
   facilitates the establishment of a set of paths satisfying certain
   constraints [6].  Such a kind of path, called a constraint-based
   routing label-switched path (CRLSP), is conceptually very similar to
   a virtual-path connection in an ATM network for traffic engineering
   purposes.  For example, packets belonging to different traffic flows
   can be classified and routed through different CRLSPs at the ingress
   LSRs of an MPLS-capable domain.  This enables the implementation of
   connection control and resource allocation functions on aggregated
   groups of traffic flows, instead of on individual flows.  Such a
   scheme allows support for different classes of service [6, 7] and
   fits well with the Differentiated Services (DiffServ) architecture
   [8, 9].  Note that DiffServ is also achievable by network-layer
   forwarding, albeit with a different mechanism for classifying
   traffic into queues at each hop for QoS [10].

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   Similar to ATM virtual paths, either administrative provisioning or
   network signaling can set up CRLSPs.  Two signaling protocols are
   currently proposed for explicitly and dynamically propagating both
   connectivity and QoS information across MPLS domains.  They are
   based on extensions to RSVP [11], and to the Label Distribution
   Protocol (LDP) [12], respectively.  For large networks, an essential
   requirement for these protocols is their scalability, in terms of
   the number of signaling messages and their computational
   requirements, with network growth.  In addition, to minimize the
   overheads associated with the management of CRLSPs, it may be
   desirable to conserve CRLSP usage.

   The ability of MPLS to set up explicitly routed CRLSPs permits
   source-node control, i.e., source routing, to operate efficiently.
   This provides network administrators the capability to steer traffic
   on desired paths, which may be arbitrary non-shortest paths.  Such
   flexibility to direct the traffic to follow engineered paths through
   a network offers a number of advantages, e.g., load sharing across
   multiple paths, and shifting traffic away from congested links.
   Conventional IP routers achieve a somewhat similar effect by either
   using the equal-cost multipath option of OSPF [13, 14] to distribute
   traffic as evenly as possible among a selected set of paths with the
   same cost, or by using IP tunnels to distribute traffic across
   alternate paths through some intermediate destinations.  (IP
   tunneling, as a means to alter the normal network-layer forwarding,
   is a datagram encapsulation technique that allows the specification
   of a tunnel's endpoints, but not the path taken by the tunnel [15].)
   Network-layer forwarding, such as that based on OSPF routing, also
   offers some form of load balancing by appropriately adjusting the
   link costs to trigger some traffic shift.  For example, by using
   this method through a software tool called the NetScope [16], a
   network operator can reconfigure network-layer routing for network
   optimization and performance debugging.  Given traffic demands, a
   technique for selecting link costs to optimize OSPF routing is
   presented in [17].  However, further investigations may be needed to
   apply this technique for routing in an operational network where
   traffic, and perhaps capacity (e.g., because of failure), is
   dynamically changing.

   Because destination-based routing does not provide a network
   operator with a precise control of the paths used for traffic flows,
   it is not easy to obtain network-wide traffic demands from the local
   interface measurements taken by different IP routers.  As explained
   in [18], information from diverse network measurements and various
   configuration files are needed to infer the traffic volume.  Based
   on flow-level measurements, this reference describes how to
   determine the traffic volume from an ingress link to a set of egress
   links by validating and joining various data sets together.  The
   ability of MPLS to use fixed preferred paths for routing traffic,
   so-called route pinning, gives the means to measure and capture the
   statistics of the traffic flows more readily.  This can be used to
   derive point-to-point demands as suggested in [19], but may also

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   help to correlate the data to derive the type of point-to-multipoint
   demands as described in [18].  As a result, there is the potential
   to develop more refined measurement technology so as to obtain a
   more accurate estimation and characterization of the traffic demands
   and related statistics for network planning and traffic engineering
   purposes.  Path-based measurements may also enable the development
   of methodologies for such functions as admission control and
   performance verification of delivered service.

   The relative merits of MPLS versus network-layer routing/forwarding
   notwithstanding, MPLS does offer a standardized set of basic
   mechanisms that can be used to facilitate traffic engineering.
   Through these mechanisms, a variety of routing policies can be
   accommodated in a unified manner.  However, to fully realize the
   potential of MPLS in terms of its generality and flexibility,
   operational processes for route configuration must be developed.  In
   particular, algorithms are needed: (1) for selecting the CRLSPs that
   satisfy traffic engineering requirements and other constraints (such
   as routing policy), (2) for distributing traffic to the selected
   CRLSPs so as to minimize the possibility for congestion, and (3) for
   managing network resources so that the QoS for different services
   can be supported.  Topics related to this aspect are to be discussed
   in what follows.


3. Traffic Engineering of IP-based Networks

   The issue of IP network traffic engineering has been addressed by
   two recent documents [20, 21].  As defined in [20], Internet traffic
   engineering is "that aspect of Internet network engineering that
   deals with the issue of performance evaluation and performance
   optimization of operational IP networks."  Since network congestion
   is a primary cause of performance degradation, a major objective of
   traffic engineering is to increase the efficiency of resource
   utilization while minimizing the possibility of congestion through
   capacity and traffic management.  Reference [20] also includes a
   discussion of requirements for routing, traffic mapping,
   measurement, survivability, and other attributes, from the
   perspective of traffic engineering.

   The interactions between traffic and capacity management in
   controlling a networkÆs response to traffic demands and network
   failures are further explored in [21].  Real-time traffic management
   functions such as routing control, path selection, and resource
   management, ensures that performance objectives are met under all
   conditions including load shifts and failures.  Capacity management,
   through control of network design, ensures that network provisioning
   meets performance objectives for a given set of traffic demands at
   minimum cost.

   A global problem of network engineering is the choice and
   implementation of a specific routing strategy for the selection of
   paths for carrying traffic.  Reference [21] provides an overview and

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   categorization of various routing methods, as well as routing table
   management methods for different network types and their
   interworking with each other.  Also described are resource
   management methods to achieve QoS objectives, such as connection
   admission control and bandwidth reservation.

   Taking account of the provisioned network capacity, routing patterns
   (i.e., path sets and rules for path selection) are designed for
   different traffic streams between different source-destination node
   pairs.  Periodically or possibly on a real-time basis, these routing
   patterns may be adjusted as necessary to correct service problems.
   An iterative network design process encompassing both routing-
   pattern design and capacity allocation is used to determine the
   minimum network capacity required to meet the performance objectives
   for given traffic demands.

   Reference [21] also presents a set of traffic engineering
   operational requirements.  For example, network management controls
   such as call gapping can be used to assure acceptable network
   performance in case of overload or failures.


4. Capacity Engineering

   According to ITU-T Recommendation E.600 [22], traffic engineering
   includes measurements, forecasting, planning, dimensioning, control,
   and performance monitoring.  Particular emphasis is placed on the
   control of resource allocation and the use of appropriate traffic
   models to size the different network elements so that the given
   performance criteria are satisfied in the support of given traffic
   demands with cost-effective and efficient resource usage.
   Specifically, traffic engineering has a goal of ensuring
   trafficability performance objectives for telecommunications
   services.  Trafficability performance is defined in Recommendation
   E.800 [23] as follows.  For each individual network element or
   functional subsystem, it is the ability of the element to meet a
   traffic demand of a given size and other characteristics, under
   given internal conditions.  These internal conditions may be, e.g.,
   any combination of faulty and not faulty parts within the element.

   Thus, trafficability performance has a direct impact on the
   accessibility, retainability, and integrity of any given service
   offered by a network; it is one of the major factors in QoS.
   Service accessibility refers to the ability of a service to be
   obtained, within specified tolerances and other given conditions,
   when requested by the user.  Service retainability refers to the
   ability of a service, once obtained, to continue to be provided
   under given conditions for a requested duration.  Service integrity
   refers to the degree to which a service is provided without
   excessive impairments, once obtained.

   Generally, trafficability performance is an attribute of network
   performance and can be described in terms of measures such as losses

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   and delays.  However, E.800 has not explicitly provided any specific
   measures for trafficability performance.

   In this document, the focus is primarily on the dimensioning aspect
   of traffic engineering and its related tasks.  In mapping given user
   demands onto network resources, network dimensioning involves the
   sizing of the network elements, such as links and buffers, so that
   performance objectives can be met at minimum cost.  Thus, two major
   inputs to the dimensioning process are characterization of user
   demands and specification of performance objectives.  (While cost is
   an important factor, the development of cost models will not be
   dealt with in this document.)  The term capacity engineering is used
   here to cover this subset of traffic engineering tasks related to
   dimensioning.  These tasks are covered in more detail in the next
   three sections.


5. Traffic Demand Characterization

   Typically, dimensioning procedures are based on models that
   approximate the statistical behavior of network traffic in large
   populations of users.  To allow straightforward characterization of
   the traffic demands, these models necessarily adopt some simplifying
   assumptions concerning the usually complicated traffic processes,
   such as the arrival patterns of flows and the distribution of flow
   sizes.  For these assumptions to be relevant and applicable, they
   must give rise to statistical patterns that closely approximate the
   behavior of aggregate traffic flows in operational networks.
   Traffic data are collected to validate these assumptions, with
   modifications being made when needed.  Additionally, traffic
   measurements are used to estimate offered load and to provide
   forecasting of future demands for capacity planning purposes.
   Forecasting and planning may result in capacity augmentation or may
   lead to the introduction of new technology and architecture.

   Thus, a first step in the dimensioning process is to develop user
   demand models as input to characterize the offered load to the
   network.  In the context of an ATM-based B-ISDN, ITU-T
   Recommendation E.716 [24] describes the characterization of user
   demand as manifested at the user-network interface.  Since a CRLSP
   in MPLS is conceptually similar to a virtual-path connection in ATM
   for traffic engineering purposes, the methodology of E.716, when
   suitably modified and extended, may be applicable to MPLS-based IP
   networks.  Further investigation of this feasibility is needed,
   especially to account for the effects of closed-loop adaptive
   controls as in a TCP connection.

   To allow the characterization of traffic offered to an IP-based
   network, user demands may be modeled as an arrival process of
   demands for IP-based services of different types.  Each such service
   demand typically generates a set of flows [25, 26], with a flow
   being a sequence of temporally correlated packets that share some
   common properties.  These properties usually include the source and

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   destination IP addresses, transport-layer application port numbers,
   and possibly others such as Type of Service.  Flows are terminated
   either by timeout or through some protocol-specific events.  For
   traffic engineering purposes, a flow in a connectionless network is
   analogous to a connection in a connection-oriented network.
   Reference [27] proposes that traffic controls be applied at the flow
   level to provide QoS guarantees.

   As each service demand generates a set of flows, each service type
   may be defined by a set of flow attributes and by a flow pattern as
   follows.  (1) Flow attributes are those attributes of the service
   demand that identify the resources needed by the service demand in
   the network.  These may include, e.g., access channel rate,
   communication configuration such as point-to-point or multipoint,
   and traffic conditioning agreements as defined in DiffServ [9].  (2)
   A flow pattern describes the packet arrival process in a flow
   through a set of traffic variables.  E.716 presents four approaches
   for defining these traffic variables to describe the transient
   nature of rate variations.  For example, they may be related to the
   burst structure of the packet flow, the number of packet arrivals in
   time intervals of specified length, packet interarrival time, or the
   number of packet arrivals exceeding a given rate.  (Currently,
   models that describe the self-similar nature of IP traffic have been
   proposed in the literature.  The applicability of these models, and
   the incorporation of the effect of self-similarity into models that
   capture the burstiness characteristics of source traffic for
   capacity engineering purposes, are for further study.)

   To recapitulate, a set of flow attributes and traffic variables may
   be used together to characterize a particular service type by
   setting appropriate values for the parameters.  Depending on the
   different values chosen for these attributes and variables, the
   number of service types can potentially be very large.  To minimize
   the effort of traffic engineering, especially in the initial stage
   of deployment, it may be desirable to limit the total number of
   service types.  For example, service types with similar values may
   possibly be combined to form one representative type that captures
   the salient features essential for dimensioning.


6. Performance Objectives and Reference Connections

   Performance objectives can be viewed from two perspectives: the user
   and the network service provider.  Quality of service (QoS), which
   is performance perceivable by a user of a service, expresses the
   user's degree of satisfaction of the service [22, 23].  Thus, QoS
   parameters focus on performance effects that are observable at the
   service access points and network interfaces, rather than their
   causes within the network [28].  Different service types usually
   have different QoS requirements.  This allows a network provider to
   provide different treatment to different service types, to gain
   higher resource utilization.


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   Grade of service (GoS) is a number of traffic engineering parameters
   to provide a measure of adequacy of a group of resources under
   specified conditions [22].  These GoS parameters may be probability
   of blocking, probability of delay, etc.  They are essential for
   network internal design and operation, as well as specification of
   component performance.  The latter is related to the trafficability
   performance described previously.  As an example, an important
   application of MPLS is to provide Virtual Private Network (VPN)
   services [29, 30].  Here, CRLSPs can possibly be used to emulate
   private lines by isolating VPNs from one another and by offering
   various types of QoS guarantees [31].  In particular, in the
   provision for resource allocation requests (such as for virtual
   leased line service) with customer-specific minimum bandwidth
   guarantees by bandwidth routing, a major GoS parameter will be the
   probability of blocking for these requests.

   Based on a given set of QoS requirements, a set of GoS parameters
   are selected and defined on an end-to-end basis within the network
   boundary, for each major service category provided by a network.
   The selected GoS parameters are specified in such a way that the GoS
   can be derived at well-defined reference points, i.e., traffic
   significant points.  This is to allow the partitioning of end-to-end
   GoS objectives to obtain the GoS objectives for each network stage
   or component, on the basis of some well-defined reference
   connections.

   As defined in E.600, for traffic engineering purposes, a connection
   is an association of resources providing means for communication
   between two or more devices in, or attached to, a telecommunication
   network.  There can be different types of connections as the number
   and types of resources in a connection may vary.  Therefore, the
   concept of a reference connection is used to identify representative
   cases of the different types of connections without involving the
   specifics of their actual realizations by different physical means.

   Typically, different network segments are involved in the path of a
   connection.  For example, a connection may be local, national, or
   international.  The purposes of reference connections are for
   clarifying and specifying traffic performance issues at various
   interfaces between different network domains.  Each domain may
   consist of one or more service provider networks.  Recommendation
   E.651 [32] specifies reference connections for IP-access networks.
   Other reference connections are to be specified.

   From the QoS objectives, a set of end-to-end GoS parameters and
   their objectives for different reference connections are derived.
   For example, end-to-end connection blocking probability and end-to-
   end packet transfer delay may be relevant GoS parameters.  The GoS
   objectives should be specified with reference to traffic load
   conditions, such as under normal and high load conditions.  The end-
   to-end GoS objectives are then apportioned to individual resource
   components of the reference connections for dimensioning purposes.
   In an operational network, to ensure that the GoS objectives have

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   been met, performance measurements and performance monitoring are
   required.


7. Network Dimensioning

   As discussed previously, network dimensioning involves the optimal
   (e.g., minimum cost) sizing of the network elements to accommodate
   given traffic demands, while meeting performance objectives.  In
   using MPLS, this means the assignment of resources such as bandwidth
   to a set of pre-selected CRLSPs for carrying traffic, and mapping
   the logical network of CRLSPs onto a physical network of links with
   capacity constraints.  The dimensioning process also determines the
   link capacity parameters or thresholds associated with the use of
   some bandwidth reservation scheme for service protection.  Service
   protection controls the GoS for certain service types by restricting
   access to bandwidth, or by giving priority access to one type of
   traffic over another.  Such methods are essential, e.g., to
   guarantee a minimum amount of resources for connections with
   expected short duration, to improve the blocking probabilities for
   connections with high bandwidth requirements, or to maintain network
   stability by preventing GoS degradation in case of a local overload.

   In performing the task of dimensioning, it is assumed that a network
   topology, both at the logical and physical levels, has been defined.
   This is because the layout of a network is usually influenced by
   other factors, such as the network providerÆs policy/administrative
   constraints, or considerations of an existing network.  Also, it is
   assumed that the network is available, i.e., it does not consider
   network equipment in a failure state.

   Routing deals with the selection of network paths for connection
   requests.  To simplify the dimensioning process, a routing-pattern
   with pre-determined paths for different traffic streams is usually
   assumed.  (This may include the use of dynamic routing, see E.525
   [33].)  As described previously, the process of routing-pattern
   design and dimensioning is iterated until an optimal design is
   reached.

   The series of ITU-T Recommendations E.735-7 [34, 35, 36] presents a
   set of general principles and methods for dimensioning ATM-based B-
   ISDNs.  The notion of Equivalent Cell Rate (ECR) has been used
   effectively therein for dimensioning purposes.  The ECR captures the
   effects of expected traffic mix, cell-level control mechanisms,
   priority scheduling, bandwidth and buffer capacity limitations,
   thereby characterizing the estimated amount of resources that needs
   to be allocated to a connection to satisfy the specified cell-level
   GoS objectives.  Borrowing from this technique, it may be useful to
   define some Equivalent Bandwidth parameter for dimensioning IP-based
   networks.  Further studies are needed for its definition.

   Assuming that connection blocking probability is the only GoS
   parameter at the connection level, and using ECR to account for

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   cell-level performance, E.737 presents several iterative methods for
   dimensioning.  To reduce computational complexity, approximation
   methods based on the independence assumption and the principle of
   decomposition may be developed.  For example, if the capacity of a
   link can be considered as well delimited, independent of the traffic
   carried by other links, then the global end-to-end decision on
   connection admission can be decomposed into local decisions.  These
   techniques may be applicable to the dimensioning of CRLSPs in an
   MPLS-based network, e.g., for the provision of the previously
   described VPN services.


8. Proposed Work Items

   From the above discussion, here is a partial list of work items for
   further study:

   1. Use of path-based measurements to help determine traffic demands
   for traffic engineering, admission control, and performance
   verification of delivered service
   2. Algorithms to select CRLSPs for traffic distribution in the
   support of QoS
   3. A set of equivalent bandwidth definitions for various service
   types for dimensioning purposes


9. Security Considerations

   Security considerations are not addressed in this version of the
   draft.


References

   1  E.C. Rosen, A. Viswanathan, and R. Callon, ôMultiprotocol Label
      Switching Architecture,ö Internet-Draft, Work in Progress, August
      1999.

   2  R. Callon, P. Doolan, N. Feldman, A. Fredette, G. Swallow, and A.
      Viswanathan, ôA Framework for Multiprotocol Label Switching,ö
      Internet-Draft, Work in Progress, September 1999.

   3  G. Huston, ôNext Steps for the IP QoS Architecture,ö Internet-
      Draft, Work in Progress, June 2000.

   4  W.S. Lai, ôPacket Forwarding,ö IEEE Communications Magazine, July
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   5  A. Viswanathan, N. Feldman, Z. Wang, and R. Callon, ôEvolution of
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   6  D. Awduche, J. Malcolm, J. Agogbua, M. OÆDell, and J. McManus,
      ôRequirements for Internet Traffic Engineering Over MPLS,ö RFC
      2702, September 1999.





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   7  T. Li and Y. Rekhter, ôA Provider Architecture for Differentiated
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   8  K. Nichols, S. Blake, F. Baker, and D. Black, ôDefinition of the
      Differentiated Services Field (DS Field) in the IPv4 and IPv6
      Headers,ö RFC 2474, December 1998.

   9  S. Blake, D. Black, M. Carlson, E. Davies, Z. Wang, and W. Weiss,
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   10 G. Armitage, ôMPLS: The Magic Behind the Myths,ö IEEE
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   11 D.O. Awduche, L. Berger, D.H. Gan, T. Li, G. Swallow, and V.
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   12 B. Jamoussi (Editor), ôConstraint-Based LSP Setup Using LDP,ö
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   13 J. Moy, ôOSPF Version 2,ö RFC 2328, April 1998.

   14 C.E. Hopps, ôAnalysis of an Equal-Cost Multi-Path Algorithm,ö
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   15 C. Perkins, ôIP Encapsulation Within IP,ö RFC 2003, October 1996.
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   16 A. Feldmann, A. Greenberg, C. Lund, N. Reingold, and J. Rexford,
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   17 B. Fortz and M. Thorup, ôInternet Traffic Engineering by
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   18 A. Feldmann, A. Greenberg, C. Lund, N. Reingold, J. Rexford, and
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   19 X. Xiao, A. Hannan, B. Bailey, and L.M. Ni, ôTraffic Engineering
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   20 D.O. Awduche, A. Chiu, A. Elwalid, I. Widjaja, and X. Xiao, ôA
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      in Progress, May 2000.

   21 ITU-T Draft Recommendation E.TE, ôTraffic Engineering and QoS
      Methods for IP-, ATM-, and TDM-Based Multiservice Networks,ö
      March 2000.  A more up-to-date version of this document appears
      as Internet-Draft <draft-ash-te-qos-routing-01.txt>, July 2000,
      (Contact: G. Ash).

   22 ITU-T Recommendation E.600, ôTerms and Definitions of Traffic
      Engineering,ö March 1993.

   23 ITU-T Recommendation E.800, ôTerms and Definitions Related to
      Quality of Service and Network
      Performance Including Dependability,ö August 1994.

   24 ITU-T Recommendation E.716, ôUser Demand Modelling in Broadband-
      ISDN,ö October 1996.

   25 K.C. Claffy, H. Braun, and G.C. Polyzos, ôA Parameterizable
      Methodology for Internet Traffic Flow Profiling, ô IEEE JSAC,
      vol. 13, No. 8, October 1995.


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               Capacity Engineering of IP/MPLS Networks      July 2000



   26 A. Feldmann, J. Rexford, and R. Caceres, ôEfficient Policies for
      Carrying Web Traffic Over Flow-Switched Networks,ö IEEE/ACM
      Transactions on Networking, December 1998.

   27 J.W. Roberts and S. Oueslati-Boulahia, ôQuality of Service by
      Flow Aware Networking,ö to appear in Philosophical Transactions.

   28 ITU-T Recommendation E.430, ôQuality of Service Framework,ö
      June1992.

   29 E.C. Rosen, S.J. Brannon, M. Carugi, C.J. Chase, E. Dean, P.
      Hitchin, M. Leelanivas, L. Martini, V. Srinivasasn, and A.
      Vedrenne, ôBGP/MPLS VPNs,ö Internet-Draft, Work in Progress, May
      2000.

   30 K. Muthukrishnan and A. Malis, ôA Core MPLS IP VPN Architecture,ö
      Internet-Draft, Work in Progress, May 2000.

   31 B. Gleeson, A. Lin, J. Heinanen, G. Armitage, and A. Malis, ôA
      Framework for IP Based Virtual Private Networks,ö RFC 2764,
      February 2000.

   32 ITU-T Recommendation E.651, ôReference Connections for Traffic
      Engineering of IP Access Networks,ö March 2000.

   33 ITU-T Recommendation E.525, ôDesigning Networks to Control Grade
      of Service,ö June 1992.

   34 ITU-T Recommendation E.735, ôFramework for Traffic Control and
      Dimensioning in B-ISDN,ö May 1997.

   35 ITU-T Recommendation E.736, ôMethods for Cell Level Traffic
      Control in B-ISDN,ö May 1997.

   36 ITU-T Recommendation E.737, ôDimensioning Methods for B-ISDN,ö
      May 1997.


Acknowledgments

   The support of Gerald Ash on this work and his comments are much
   appreciated.  An earlier version of this document was presented to
   the ITU-T Study Group 2, Working Party 3 (WP 3/2: Traffic
   Engineering) meeting in March 2000.  The author is most grateful of
   the support and comments from WP 3/2 members, in particular,
   Toshikane Oda, Bruce Pettitt, James Roberts, and Manuel Villen-
   Altamirano.  The author would also like to thank the input from
   Christopher Chase, Jennifer Rexford, and Herbert Shulman.


Author's Addresses

   Wai Sum Lai
   AT&T Labs
   Room D5-3D18
   200 Laurel Avenue
   Middletown, New Jersey 07748, USA
   Phone: 732-420-3712
   Email: wlai@att.com


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               Capacity Engineering of IP/MPLS Networks      July 2000



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