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Versions: 00 01 02 03 04 05 06 rfc4126                                  
Network Working Group                                        Jerry Ash
Internet Draft                                                    AT&T
Category: Experimental
<draft-ietf-tewg-diff-te-mar-02.txt>
Expiration Date:  March 2004
                                                         October, 2003


    Max Allocation with Reservation Bandwidth Constraint Model for
               MPLS/DiffServ TE & Performance Comparisons

                  <draft-ietf-tewg-diff-te-mar-02.txt>

Status of this Memo

   This document is an Internet-Draft and is in full conformance with
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Abstract

This document complements the DiffServ-aware MPLS TE (DSTE) requirements
document by giving a functional specification for the Maximum Allocation
with Reservation (MAR) bandwidth constraint model.  Assumptions,
applicability, and examples of the operation of the MAR bandwidth
constraint model are presented.  MAR performance is analyzed relative to
the criteria for selecting a bandwidth constraint model, in order to
provide guidance to user implementation of the model in their networks.

Table of Contents

   1. Introduction
   2. Definitions
   3. Assumptions & Applicability
   4. Functional Specification of the MAR Bandwidth Constraint Model
   5. Setting Bandwidth Constraints
   6. Example of MAR Operation
   7. Summary
   8. Security Considerations
   9. Acknowledgments
   10. Normative References
   11. Informative References
   12. Authors' Addresses
   ANNEX A. MAR Operation & Performance Analysis

Specification of Requirements

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 [RFC2119].

1. Introduction

DiffServ-aware MPLS traffic engineering (DSTE) requirements and protocol
extensions are specified in [DSTE-REQ, DSTE-PROTO]. A requirement for
DSTE implementation is the specification of bandwidth constraint models
for use with DSTE.  The bandwidth constraint model provides the 'rules'
to support the allocation of bandwidth to individual class types (CTs).
CTs are groupings of service classes in the DSTE model, which are
provided separate bandwidth allocations, priorities, and QoS objectives.
 Several CTs can share a common bandwidth pool on an integrated,
multiservice MPLS/DiffServ network.

This document is intended to complement the DSTE requirements document
[DSTE-REQ] by giving a functional specification for the Maximum
Allocation with Reservation (MAR) bandwidth constraint model.  Examples
of the operation of the MAR bandwidth constraint model are presented.
MAR performance is analyzed relative to the criteria for selecting a
bandwidth constraint model, in order to provide guidance to user
implementation of the model in their networks.

Two other bandwidth constraint models are being specified for use in
DSTE:

1. maximum allocation model (MAM) [MAM] - the maximum allowable
bandwidth usage of each CT is explicitly specified.
2. Russian doll model (RDM) [RDM] - the maximum allowable bandwidth
usage is done cumulatively by grouping successive CTs according to
priority classes.

MAR is similar to MAM in that a maximum bandwidth allocation is given to
each CT.  However, through the use of bandwidth reservation and
protection mechanisms, CTs are allowed to exceed their bandwidth
allocations under conditions of no congestion but revert to their
allocated bandwidths when overload and congestion occurs.

All bandwidth constraint models should meet these objectives:

1. applies equally when preemption is either enabled or disabled (when
preemption is disabled, the model still works 'reasonably' well),
2. Bandwidth efficiency, i.e., good bandwidth sharing among CTs under
both normal and overload conditions,
3. bandwidth isolation, i.e., a CT cannot hog the bandwidth of another
CT under overload conditions,
4. protection against QoS degradation, at least of the high-priority CTs
(e.g. high-priority voice, high-priority data, etc.), and
5. reasonably simple, i.e., does not require additional IGP extensions
and minimizes signaling load processing requirements.

In Annex A modeling analysis is presented which shows that the MAR model
meets all these objectives, and provides good network performance
relative to MAM and full sharing models, under normal and abnormal
operating conditions.  It is demonstrated that simultaneously achieves
bandwidth efficiency, bandwidth isolation, and protection against QoS
degradation without preemption.

In Section 3 we give the assumptions and applicability, in Section 4 a
functional specification of the MAR bandwidth constraint model, and in
Section 5 we give examples of its operation.  In Annex A, MAR
performance is analyzed relative to the criteria for selecting a
bandwidth constraint model, in order to provide guidance to user
implementation of the model in their networks.

2. Definitions

For readability a number of definitions from [DSTE-REQ, DSTE-PROTO] are
repeated here:

Traffic Trunk: an aggregation of traffic flows of the same class (i.e.
which are to be treated equivalently from the DSTE perspective) which
are placed inside an LSP.

Class-Type (CT): the set of Traffic Trunks crossing a link that is
governed by a specific set of Bandwidth constraints. CT is used for the
purposes of link bandwidth allocation, constraint based routing and
admission control. A given Traffic Trunk belongs to the same CT on all
links.

Up to 8 CTs (MaxCT = 8) are supported.  They are referred to as CTc, 0
<= c <= MaxCT-1 = 7.  Each CT is assigned either a Bandwidth
Constraint, or a set of Bandwidth Constraints.  Up to 8 Bandwidth
Constraints (MaxBC = 8) are supported and they are referred to as BCc,
0 <= c <= MaxBC-1 = 7.

TE-Class: A pair of: i. a CT ii. a preemption priority allowed for that
CT. This means that an LSP transporting a Traffic Trunk from that CT can
use that preemption priority as the set-up priority, as the holding
priority or both.

MAX_RESERVABLE_BWk: maximum reservable bandwidth on link k specifies the
maximum bandwidth that may be reserved; this may be greater than the
maximum link bandwidth in which case the link may be oversubscribed
[KATZ-YEUNG].

BCck: bandwidth constraint for CTc on link k = allocated (minimum
guaranteed) bandwidth for CTc on link k (see Section 4).

RBW_THRESk: reservation bandwidth threshold for link k (see Section 4).

RESERVED_BWck: reserved bandwidth-in-progress on CTc on link k (0 <3D c
<3D MaxCT-1), RESERVED_BWck 3D total amount of the bandwidth reserved
by all the established LSPs which belong to CTc.

UNRESERVED_BWck: unreserved link bandwidth on CTc on link k specifies
the amount of bandwidth not yet reserved for CTc, UNRESERVED_BWck 3D
MAX_RESERVABLE_BWk - sum [RESERVED_BWck (0 <3D c <3D MaxCT-1)].

A number of recovery mechanisms under investigation in the IETF take
advantage of the concept of bandwidth sharing across particular sets of
LSPs. "Shared Mesh Restoration" in [GMPLS-RECOV] and "Facility-based
Computation Model" in [MPLS-BACKUP] are example mechanisms which
increase bandwidth efficiency by sharing bandwidth across backup LSPs
protecting against independent failures. To ensure that the notion of
RESERVED_BWck introduced in [DSTE-REQ] is compatible with such a concept
of bandwidth sharing across multiple LSPs, the wording of the definition
provided in [DSTE-REQ] is generalized.  With this generalization, the
definition is compatible with Shared Mesh Restoration defined in
[GMPLS-RECOV], so that DSTE and Shared Mesh Protection can operate
simultaneously, under the assumption that Shared Mesh Restoration
operates independently within each DSTE Class-Type and does not operate
across Class-Types.  For example, backup LSPs protecting primary LSPs of
CTc must also belong to CTc; excess traffic LSPs sharing bandwidth with
backup LSPs of CTc must also belong to CTc.

3. Assumptions & Applicability

In general, DSTE is a bandwidth allocation mechanism, for different
classes of traffic allocated to various CTs (e.g., voice, normal data,
best-effort data).  Network operations functions such as capacity
design, bandwidth allocation, routing design, and network planning are
normally based on traffic measured load and forecast [ASH1].

As such, the following assumptions are made according to the operation
of MAR:

1. connection admission control (CAC) allocates bandwidth for network
flows/LSPs according to the traffic load assigned to each CT, based on
traffic measurement and forecast.
2. CAC could allocate bandwidth per flow, per LSP, per traffic trunk, or
otherwise.  That is, no specific assumption is made on a specific CAC
method, only that CT bandwidth allocation is related to the
measured/forecast traffic load, as per assumption #1.
3. CT bandwidth allocation is adjusted up or down according to
measured/forecast traffic load.  No specific time period is assumed for
this adjustment, it could be short term (hours), daily, weekly, monthly,
or otherwise.
4. Capacity management and CT bandwidth allocation thresholds (e.g.,
BCc) are designed according to traffic load, and are based on traffic
measurement and forecast.  Again, no specific time period is assumed for
this adjustment, it could be short term (hours), daily, weekly, monthly,
or otherwise.
5. No assumption is made on the order in which traffic is allocated to
various CTs, again traffic allocation is assumed to be based only on
traffic load as it is measured and/or forecast.
6. If link bandwidth is exhausted on a given path for a flow/LSP/traffic
trunk, alternate paths may be attempted to satisfy CT bandwidth
allocation.

Note that the above assumptions are not unique to MAR, but are generic,
common assumptions for all BC models.

4. Functional Specification of the MAR Bandwidth Constraint Model

A DSTE LSR implementing MAR MUST support enforcement of bandwidth
constraints in compliance with the specifications in this Section.

In the MAR bandwidth constraint model, the bandwidth allocation control
for each CT is based on estimated bandwidth needs, bandwidth use, and
status of links.  The LER makes needed bandwidth allocation changes, and
uses [RSVP-TE], for example, to determine if link bandwidth can be
allocated to a CT. Bandwidth allocated to individual CTs is protected as
needed but otherwise shared. Under normal non-congested network
conditions, all CTs/services fully share all available bandwidth.  When
congestion occurs for a particular CTc, bandwidth reservation acts to
prohibit traffic from other CTs from seizing the allocated capacity for
CTc.

On a given link k, a small amount of bandwidth RBW_THRESk, the
reservation bandwidth threshold for link k, is reserved and governs the
admission control on link k.  Also associated with each CTc on link k
are the allocated bandwidth constraints BCck to govern bandwidth
allocation and protection.  The reservation bandwidth on a link,
RBW_THRESk, can be accessed when a given CTc has bandwidth-in-use
RESERVED_BWck below its allocated bandwidth constraint BCck.  However,
if RESERVED_BWck exceeds its allocated bandwidth constraint BCck, then
the reservation bandwidth RBW_THRESk cannot be accessed. In this way,
bandwidth can be fully shared among CTs if available, but is otherwise
protected by bandwidth reservation methods.

Bandwidth can be accessed for a bandwidth request = DBW for CTc on a
given link k based on the following rules:

Table 1: Rules for Admitting LSP Bandwidth Request = DBW on Link k

For LSP on a high priority or normal priority CTc:
If RESERVED_BWck <= BCc: admit if DBW <= UNRESERVED_BWk
If RESERVED_BWck > BCc:  admit if DBW <= UNRESERVED_BWk - RBW_THRESk

For LSP on a best-effort priority CTc:
allocated bandwidth BCc = 0;
DiffServ queuing admits BE packets only if there is available link
bandwidth;

The normal semantics of setup and holding priority are applied in the
MAR bandwidth constraint model, and cross-CT preemption is permitted
when preemption is enabled.

The bandwidth allocation rules defined in Table 1 are illustrated with
an example in Section 6 and simulation analysis in ANNEX A.

5. Setting Bandwidth Constraints

For a normal priority CTc, the bandwidth constraints BCck on link k are
set by allocating the maximum reservable bandwidth (MAX_RESERVABLE_BWk)
in proportion to the forecast or measured traffic load bandwidth
TRAF_LOAD_BWck for CTc on link k.  That is:

PROPORTIONAL_BWck = TRAF_LOAD_BWck/[sum {TRAF_LOAD_BWck, c=0,MaxCT-1}] X
                    MAX_RESERVABLE_BWk

For normal priority CTc:
BCck = PROPORTIONAL_BWck

For a high priority CT, the bandwidth constraint BCck is set to a
multiple of the proportional bandwidth.  That is:

For high priority CTc:
BCck = FACTOR X PROPORTIONAL_BWck

where FACTOR is set to a multiple of the proportional bandwidth (e.g.,
FACTOR = 2 or 3 is typical).  This results in some 'over-allocation'
of the maximum reservable bandwidth, and gives priority to the high
priority CTs.  Normally the bandwidth allocated to high priority CTs
should be a relatively small fraction of the total link bandwidth, a
maximum of 10-15 percent being a reasonable guideline.

As stated in Section 4, the bandwidth allocated to a best-effort
priority CTc should be set to zero.  That is:

For best-effort priority CTc:
BCck = 0

6. Example of MAR Operation

In the example, assume there are three class-types: CT0, CT1, CT2.  We
consider a particular link with

MAX-RESERVABLE_BW = 100

And with the allocated bandwidth constraints set as follows:

BC0 = 30
BC1 = 20
BC2 = 20

These bandwidth constraints are based on the normal traffic loads, as
discussed in Section 5.  With MAR, any of the CTs is allowed to exceed
its bandwidth constraint BCc as long a there is at least RBW_THRES
(reservation bandwidth threshold on the link) units of spare bandwidth
remaining.  Let's assume

RBW_THRES = 10

So under overload, if

RESERVED_BW0 = 50
RESERVED_BW1 = 30
RESERVED_BW2 = 10

Therefore, for this loading

UNRESERVED_BW = 100 - 50 - 30 - 10 = 10

CT0 and CT1 can no longer increase their bandwidth on the link, since
they are above their BC values and there is only RBW_THRES=10 units of
spare bandwidth left on the link.  But CT2 can take the additional
bandwidth (up to 10 units) if the demand arrives, since it is below its
BC value.

As also discussed in Section 4, if best effort traffic is present, it
can always seize whatever spare bandwidth is available on the link at
the moment, but is subject to being lost at the queues in favor of the
higher priority traffic.

Let's say an LSP arrives for CT0 needing 5 units of bandwidth (i.e., DBW
= 5).  We need to decide based on Table 1 whether to admit this LSP or
not.  Since for CT0

RESERVED_BW0 > BC0 (50 > 30), and
DBW > UNRESERVED_BW - RBW_THRES (i.e., 5 > 10 - 10)

Table 1 says the LSP is rejected/blocked.

Now let's say an LSP arrives for CT2 needing 5 units of bandwidth (i.e.,
DBW = 5).  We need to decide based on Table 1 whether to admit this
LSP or not.  Since for CT2

RESERVED_BW2 < BC2 (10 < 20), and
DBW < UNRESERVED_BW (i.e., 10 - 10 < 5)

Table 1 says to admit the LSP.

Hence, in the above example, in the current state of the link and the
current CT loading, CT0 and CT1 can no longer increase their bandwidth
on the link, since they are above their BCc values and there is only
RBW_THRES=10 units of spare bandwidth left on the link.  But CT2 can
take the additional bandwidth (up to 10 units) if the demand arrives,
since it is below its BCc value.

7. Summary

The proposed MAR bandwidth constraint model includes the following: a)
allocate bandwidth to individual CTs, b) protect allocated bandwidth by
bandwidth reservation methods, as needed, but otherwise fully share
bandwidth, c) differentiate high-priority, normal-priority, and
best-effort priority services, and d) provide admission control to
reject connection requests when needed to meet performance objectives.
Modeling results presented in Annex A show that MAR bandwidth allocation
a) achieves greater efficiency in bandwidth sharing while still
providing bandwidth isolation and protection against QoS degradation,
and b) achieves service differentiation for high-priority,
normal-priority, and best-effort priority services.

8. Security Considerations

No new security considerations are raised by this document, they are the
same as in the DSTE requirements document [DSTE-REQ].

9. Acknowledgements

DSTE and bandwidth constraint models have been an active area of
discussion in the TEWG.  I would like to thank Wai Sum Lai for his
support and review of this draft.  I also appreciate helpful discussions
with Francois Le Faucheur.

10. Normative References

[DSTE-REQ] Le Faucheur, F., Lai, W., et. al., "Requirements for Support
of Diff-Serv-aware MPLS Traffic Engineering," RFC 3564, July 2003.
[DSTE-PROTO] Le Faucheur, F., et. al., "Protocol Extensions for Support
of Diff-Serv-aware MPLS Traffic Engineering," work in progress.
[KEY] Bradner, S., "Key words for Use in RFCs to Indicate Requirement
Levels", RFC 2119, March 1997.

11. Informative References

[AKI] Akinpelu, J. M., The Overload Performance of Engineered Networks
with Nonhierarchical & Hierarchical Routing, BSTJ, Vol. 63, 1984.
[ASH1] Ash, G. R., Dynamic Routing in Telecommunications Networks,
McGraw-Hill, 1998.
[ASH2] Ash, G. R., et. al., Routing Evolution in Multiservice Integrated
Voice/Data Networks, Proceeding of ITC-16, Edinburgh, June 1999.
[ASH3] Ash, G. R., Traffic Engineering & QoS Methods for IP-, ATM-, &
TDM-Based Multiservice Networks, work in progress.
[BUR] Burke, P. J., Blocking Probabilities Associated with Directional
Reservation, unpublished memorandum, 1961.
[DIFF-MPLS] Le Faucheur, F., et. al., "MPLS Support of Diff-Serv", RFC
3270, May 2002.
[DIFFSERV] Blake, S., et. al., "An Architecture for Differentiated
Services", RFC 2475, December 1998.
[DSTE-PERF] Lai, W., "Bandwidth Constraints Models for Diffserv-TE:
Performance Evaluation", work in progress.
[E.360.1 --> E.360.7] ITU-T Recommendations, "QoS Routing & Related
Traffic Engineering Methods for Multiservice TDM-, ATM-, & IP-Based
Networks".
[GMPLS-RECOV] Lang, J., et. al., "Generalized MPLS Recovery Functional
Specification", work in progress.
[KATZ-YEUNG] Katz, D., Yeung, D., Kompella, K., "Traffic Engineering
Extensions to OSPF Version 2," work in progress.
[KRU] Krupp, R. S., "Stabilization of Alternate Routing Networks",
Proceedings of ICC, Philadelphia, 1982.
[LAI] Lai, W., "Traffic Engineering for MPLS, Internet Performance and
Control of Network Systems III Conference", SPIE Proceedings Vol. 4865,
pp. 256-267, Boston, Massachusetts, USA, 29 July-1 August 2002
(http://www.columbia.edu/~ffl5/waisum/bcmodel.pdf).
[MAM] Le Faucheur, F., Lai, W., "Maximum Allocation Bandwidth
Constraints Model for Diff-Serv-aware MPLS Traffic Engineering", work in
progress.
[MPLS-BACKUP] Vasseur, J. P., et. al., "MPLS Traffic Engineering Fast
Reroute: Bypass Tunnel Path Computation for Bandwidth Protection", work
in progress.
[MUM] Mummert, V. S., "Network Management and Its Implementation on the
No. 4ESS, International Switching Symposium", Japan, 1976.
[NAK] Nakagome, Y., Mori, H., Flexible Routing in the Global
Communication Network, Proceedings of ITC-7, Stockholm, 1973.
[MPLS-ARCH] Rosen, E., et. al., "Multiprotocol Label Switching
Architecture," RFC 3031, January 2001.
[RDM] Le Faucheur, F., "Russian Dolls Bandwidth Constraints Model for
Diff-Serv-aware MPLS Traffic Engineering", work in progress.
[RFC2026] Bradner, S., "The Internet Standards Process -- Revision 3",
BCP 9, RFC 2026, October 1996.
[RSVP-TE] Awduche, D., et. al., "RSVP-TE: Extensions to RSVP for LSP
Tunnels", RFC 3209, December 2001.

11. Authors' Addresses

Jerry Ash
AT&T
Room MT D5-2A01
200 Laurel Avenue
Middletown, NJ 07748, USA
Phone: +1 732-420-4578
Email: gash@att.com

ANNEX A - MAR Operation & Performance Analysis

A.1 MAR Operation

In the MAR bandwidth constraint model, the bandwidth allocation control
for each CT is based on estimated bandwidth needs, bandwidth use, and
status of links. The LER makes needed bandwidth allocation changes, and
uses [RSVP-TE], for example, to determine if link bandwidth can be
allocated to a CT. Bandwidth allocated to individual CTs is protected as
needed but otherwise shared. Under normal non-congested network
conditions, all CTs/services fully share all available bandwidth.  When
congestion occurs for a particular CTc, bandwidth reservation acts to
prohibit traffic from other CTs from seizing the allocated capacity for
CTc.  Associated with each CT is the allocated bandwidth constraint
(BCc) to govern bandwidth allocation and protection, these parameters
are illustrated with examples in this ANNEX.

In performing MAR bandwidth allocation for a given flow/LSP, the LER
first determines the egress LSR address, service-identity, and CT.  The
connection request is allocated an equivalent bandwidth to be routed on
a particular CT. The LER then accesses the CT priority, QoS/traffic
parameters, and routing table between the LER and egress LSR, and sets
up the connection request using the MAR bandwidth allocation rules.  The
LER selects a first choice path and determines if bandwidth can be
allocated on the path based on the MAR bandwidth allocation rules given
in Section 4.  If the first choice path has insufficient bandwidth, the
LER may then try alternate paths, and again applies the MAR bandwidth
allocation rules now described.

MAR bandwidth allocation is done on a per-CT basis, in which aggregated
CT bandwidth is managed to meet the overall bandwidth requirements of CT
service needs.  Individual flows/LSPs are allocated bandwidth in the
corresponding CT according to CT bandwidth availability.  A fundamental
principle applied in MAR bandwidth allocation methods is the use of
bandwidth reservation techniques.

Bandwidth reservation gives preference to the preferred traffic by
allowing it to seize any idle bandwidth on a link, while allowing the
non-preferred traffic to only seize bandwidth if there is a minimum
level of idle bandwidth available called the reservation bandwidth
threshold RBW_THRES.  Burke [BUR] first analyzed bandwidth reservation
behavior from the solution of the birth-death equations for the
bandwidth reservation model.  Burke's model showed the relative
lost-traffic level for preferred traffic, which is not subject to
bandwidth reservation restrictions, as compared to non-preferred
traffic, which is subject to the restrictions. Bandwidth reservation
protection is robust to traffic variations and provides significant
dynamic protection of particular streams of traffic.  It is widely used
in large-scale network applications [ASH1, MUM, AKI, KRU, NAK].

Bandwidth reservation is used in MAR bandwidth allocation to control
sharing of link bandwidth across different CTs.  On a given link, a
small amount of bandwidth RBW_THRES is reserved (say 1% of the total
link bandwidth), and the reservation bandwidth can be accessed when a
given CT has reserved bandwidth-in-progress RESERVED_BW below its
allocated bandwidth BC.  That is, if the available link bandwidth
(unreserved idle link bandwidth UNRESERVED_BW) exceeds RBW_THRES, then
any CT is free to access the available bandwidth on the link.  However,
if UNRESERVED_BW is less than RBW_THRES, then the CT can utilize the
available bandwidth only if its current bandwidth usage is below the
allocated amount BC. In this way, bandwidth can be fully shared among
CTs if available, but is protected by bandwidth reservation if below the
reservation level.

Through the bandwidth reservation mechanism, MAR bandwidth allocation
also gives preference to high-priority CTs, in comparison to
normal-priority and best-effort priority CTs.

Hence, bandwidth allocated to each CT is protected by bandwidth
reservation methods, as needed, but otherwise shared.  Each LER monitors
CT bandwidth use on each CT, and determines if connection requests can
be allocated to the CT bandwidth.  For example, for a bandwidth request
of DBW on a given flow/LSP, the LER determines the CT priority (high,
normal, or best-effort), CT bandwidth-in-use, and CT bandwidth
allocation thresholds, and uses these parameters to determine the
allowed load state threshold to which capacity can be allocated.  In
allocating bandwidth DBW to a CT on given LSP, say A-B-E, each link in
the path is checked for available bandwidth in comparison to the allowed
load state.  If bandwidth is unavailable on any link in path A-B-E,
another LSP could by tried, such as A-C-D-E.  Hence determination of the
link load state is necessary for MAR bandwidth allocation, and two link
load states are distinguished: available (non-reserved) bandwidth
(ABW_STATE), and reserved-bandwidth (RBW_STATE).  Management of CT
capacity uses the link state and the allowed load state threshold to
determine if a bandwidth allocation request can be accepted on a given
CT.

A.2 Analysis of MAR Performance

In this Annex, modeling analysis is presented in which MAR bandwidth
allocation is shown to provide good network performance relative to full
sharing models, under normal and abnormal operating conditions.  A
large-scale MPLS/DiffServ TE simulation model is used, in which several
CTs with different priority classes share the pool of bandwidth on a
multiservice, integrated voice/data network.  MAR methods have also been
analyzed in practice for TDM-based networks [ASH1], and in modeling
studies for IP-based networks [ASH2, ASH3, E.360].

All bandwidth constraint models should meet these objectives:

1. applies equally when preemption is either enabled or disabled (when
preemption is disabled, the model still works 'reasonably' well),
2. Bandwidth efficiency, i.e., good bandwidth sharing among CTs under
both normal and overload conditions,
3. bandwidth isolation, i.e., a CT cannot hog the bandwidth of another
CT under overload conditions,
4. protection against QoS degradation, at least of the high-priority CTs
(e.g. high-priority voice, high-priority data, etc.), and
5. reasonably simple, i.e., does not require additional IGP extensions
and minimizes signaling load processing requirements.

The use of any given bandwidth constraint model has significant impacts
on the performance of a network, as explained later. Therefore, the
criteria used to select a model must enable us to evaluate how a
particular model delivers its performance, relative to other models. Lai
[LAI, DSTE-PERF] has analyzed the MA and RD models and provided valuable
insights into the relative performance of these models under various
network conditions.

In environments where preemption is not used, MAM is attractive because
a) it is good at achieving isolation, and b) it achieves reasonable
bandwidth efficiency with some QoS degradation of lower classes.  When
preemption is used, RDM is attractive because it can achieve bandwidth
efficiency under normal load.  However, RDM cannot provide service
isolation under high load or when preemption is not used.

Our performance analysis of MAR bandwidth allocation methods is based on
a full-scale, 135-node simulation model of a national network together
with a multiservice traffic demand model to study various scenarios and
tradeoffs [ASH3].  Three levels of traffic priority - high, normal, and
best effort -- are given across 5 CTs: normal priority voice, high
priority voice, normal priority data, high priority data, and best
effort data.

The performance analyses for overloads and failures include a) the MAR
bandwidth constraint model, as specified in Section 4, b) the MAM
bandwidth constraint model, and c) the No-DSTE bandwidth constraint
model.

The allocated bandwidth constraints for MAR are as described in Section
5:

Normal priority CTs:      BCck = PROPORTIONAL_BWk,
High priority CTs:        BCck = FACTOR X PROPORTIONAL_BWk
Best-effort priority CTs: BCck = 0

In the MAM bandwidth constraint model, the bandwidth constraints for
each CT are set to a multiple of the proportional bandwidth allocation:

Normal priority CTs:      BCck = FACTOR1 X PROPORTIONAL_BWk,
High priority CTs:        BCck = FACTOR2 X PROPORTIONAL_BWk
Best-effort priority CTs: BCck = 0

Simulations show that for MAM, the sum (BCc) should exceed
MAX_RESERVABLE_BWk for better efficiency, as follows:

1. The normal priority CTs the BCc values need to be over-allocated to
get reasonable performance.  It was found that over-allocating by 100%,
that is, setting FACTOR1 = 2, gave reasonable performance.
2. The high priority CTs can be over-allocated by a larger multiple
FACTOR2 in MAM and this gives better performance.

The rather large amount of over-allocation improves efficiency but
somewhat defeats the 'bandwidth protection/isolation' needed with a BC
model, since one CT can now invade the bandwidth allocated to another
CT.  Each CT is restricted to its allocated bandwidth constraint BCck,
which is the maximum level of bandwidth allocated to each CT on each
link, as in normal operation of MAM.

In the No-DSTE bandwidth constraint model, no reservation or protection
of CT bandwidth is applied, and bandwidth allocation requests are
admitted if bandwidth is available.  Furthermore, no queueing priority
is applied to any of the CTs in the No-DSTE bandwidth constraint model.

Table 2 gives performance results for a six-times overload on a single
network node at Oakbrook IL.  The numbers given in the table are the
total network percent lost (blocked) or delayed traffic.  Note that in
the focused overload scenario studied here, the percent lost/delayed
traffic on the Oakbrook node is much higher than the network-wide
average values given.

                                Table 2
            Performance Comparison for MAR, MAM, & No-DSTE
                   Bandwidth Constraint (BC) Models
6X Focused Overload on Oakbrook (Total Network % Lost/Delayed Traffic)

Class Type                      MAR BC  MAM BC  No-DSTE BC
                                Model   Model   Model
NORMAL PRIORITY VOICE           0.00    1.97    10.3009
HIGH PRIORITY VOICE             0.00    0.00    7.0509
NORMAL PRIORITY DATA            0.00    6.63    13.3009
HIGH PRIORITY DATA              0.00    0.00    7.0509
BEST EFFORT PRIORITY DATA       12.33   11.92   9.6509

Clearly the performance is better with MAR bandwidth allocation, and the
results show that performance improves when bandwidth reservation is
used.  The reason for the poor performance of the No-DSTE model, without
bandwidth reservation, is due to the lack of protection of allocated
bandwidth.  If we add the bandwidth reservation mechanism, then
performance of the network is greatly improved.

The simulations showed that the performance of MAM is quite sensitive to
the over-allocation factors discussed above.  For example, if the BCc
values are proportionally allocated with FACTOR1 = 1, then the results
are much worse, as shown in Table 3:

                           Table 3
     Performance Comparison for MAM Bandwidth Constraint Model
          with Different Over-allocation Factors
6X Focused Overload on Oakbrook (Total Network % Lost/Delayed Traffic)

Class Type                      (FACTOR1 = 1)   (FACTOR1 = 2)
NORMAL PRIORITY VOICE           31.69           1.9709
HIGH PRIORITY VOICE             0.00            0.0009
NORMAL PRIORITY DATA            31.22           6.6309
HIGH PRIORITY DATA              0.00            0.0009
BEST EFFORT PRIORITY DATA       8.76            11.9209


Table 4 illustrates the performance of the MAR, MAM, and No-DSTE
bandwidth constraint models for a high-day network load pattern with a
30% general overload.  The numbers given in the table are the total
network percent lost (blocked) or delayed traffic.

                                Table 4
            Performance Comparison for MAR, MAM, & No-DSTE
                   Bandwidth Constraint (BC) Models
     50% General Overload (Total Network % Lost/Delayed Traffic)

Class Type                      MAR BC  MAM BC  No-DSTE BC
                                Model   Model   Model
NORMAL PRIORITY VOICE           0.02    0.13    7.9809
HIGH PRIORITY VOICE             0.00    0.00    8.9409
NORMAL PRIORITY DATA            0.00    0.26    6.9309
HIGH PRIORITY DATA              0.00    0.00    8.9409
BEST EFFORT PRIORITY DATA       10.41   10.39   8.4009

Again, we can see the performance is always better when MAR bandwidth
allocation and reservation is used.

Table 5 illustrates the performance of the MAR, MAM, and No-DSTE
bandwidth constraint models for a single link failure scenario (3
OC-48).  The numbers given in the table are the total network percent
lost (blocked) or delayed traffic.

                                Table 5
            Performance Comparison for MAR, MAM, & No-DSTE
                   Bandwidth Constraint (BC) Models
                    Single Link Failure (3 OC-48s)
                (Total Network % Lost/Delayed Traffic)

Class Type                      MAR BC  MAM BC  No-DSTE BC
                                Model   Model   Model
NORMAL PRIORITY VOICE           0.00    0.62    0.5809
HIGH PRIORITY VOICE             0.00    0.31    0.2909
NORMAL PRIORITY DATA            0.00    0.48    0.4609
HIGH PRIORITY DATA              0.00    0.31    0.2909
BEST EFFORT PRIORITY DATA       0.12    0.72    0.6609

Again, we can see the performance is always better when MAR bandwidth
allocation and reservation is used.

Table 6 illustrates the performance of the MAR, MAM, and No-DSTE
bandwidth constraint models for a multiple link failure scenario (3
links with 3 OC-48, 3 OC-3, 4 OC-3 capacity, respectively).  The numbers
given in the table are the total network percent lost (blocked) or
delayed traffic.

                                Table 6
            Performance Comparison for MAR, MAM, & No-DSTE
                   Bandwidth Constraint (BC) Models
Multiple Link Failure (3 Links with 3 OC-48, 3 OC-3, 4 OC-3, Respectively)
                (Total Network % Lost/Delayed Traffic)

Class Type                      MAR BC  MAM BC  No-DSTE BC
                                Model   Model   Model
NORMAL PRIORITY VOICE           0.00    0.91    0.8609
HIGH PRIORITY VOICE             0.00    0.44    0.4209
NORMAL PRIORITY DATA            0.00    0.70    0.6409
HIGH PRIORITY DATA              0.00    0.44    0.4209
BEST EFFORT PRIORITY DATA       0.14    1.03    0.9809

Again, we can see the performance is always better when MAR bandwidth
allocation and reservation is used.

Lai's results [LAI, DSTE-PERF] show the trade-off between bandwidth sharing
and service protection/isolation, using an analytic model of a single
link. He shows that RDM has a higher degree of sharing than MAM.
Furthermore, for a single link, the overall loss probability is the
smallest under full sharing and largest under MAM, with RDM being
intermediate. Hence, on a single link, Lai shows that the full sharing
model yields the highest link efficiency and MAM the lowest, and that
full sharing has the poorest service protection capability.

The results of the present study show that when considering a network
context, in which there are many links and multiple-link routing paths
are used, full sharing does not necessarily lead to maximum network-wide
bandwidth efficiency.  In fact, the results in Table 4 show that the
No-DSTE model not only degrades total network throughput, but also
degrades the performance of every CT that should be protected.  Allowing
more bandwidth sharing may improve performance up to a point, but can
severely degrade performance if care is not taken to protect allocated
bandwidth under congestion.

Both Lai's study and this study show that increasing the degree of
bandwidth sharing among the different CTs leads to a tighter coupling
between CTs. Under normal loading conditions, there is adequate capacity
for each CT, which minimizes the effect of such coupling. Under overload
conditions, when there is a scarcity of capacity, such coupling can
cause severe degradation of service, especially for the lower priority
CTs.

Thus, the objective of maximizing efficient bandwidth usage, as stated
in bandwidth constraint model objectives, must be exercised with care.
Due consideration needs to be given also to achieving bandwidth
isolation under overload, in order to minimize the effect of
interactions among the different CTs. The proper tradeoff of bandwidth
sharing and bandwidth isolation needs to be achieved in the selection of
a bandwidth constraint model.  Bandwidth reservation supports greater
efficiency in bandwidth sharing while still providing bandwidth
isolation and protection against QoS degradation.

In summary, the proposed MAR bandwidth constraint model includes the
following: a) allocate bandwidth to individual CTs, b) protect allocated
bandwidth by bandwidth reservation methods, as needed, but otherwise
fully share bandwidth, c) differentiate high-priority, normal-priority,
and best-effort priority services, and d) provide admission control to
reject connection requests when needed to meet performance objectives.

In the modeling results, the MAR bandwidth constraint model compares
favorably with methods that do not use bandwidth reservation.  In
particular, some of the conclusions from the modeling are as follows:

o MAR bandwidth allocation is effective in improving performance over
methods that lack bandwidth reservation and that allow more bandwidth
sharing under congestion,
o MAR achieves service differentiation for high-priority,
normal-priority, and best-effort priority services,
o bandwidth reservation supports greater efficiency in bandwidth sharing
while still providing bandwidth isolation and protection against QoS
degradation, and is critical to stable and efficient network
performance.

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