Carrier Ethernet Over SDH

8/2/2019 Carrier Ethernet Over SDH

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Carrier Grade Ethernet versus SDH

in Optical Networks: Planning Methods

and CAPEX Comparisons

Domenico Siracusa, Guido MaierDepartment of Electronics and Information, Politecnico di Milano, Via Ponzio 34-35, 20121 Milan, Italy

Email: {siracusa,maier}@elet.polimi.it

Abstract The new Carrier Ethernet services offered byproviders require not only a huge amount of bandwidth, but alsoa more flexible access to bandwidth that the traditional trans-port networks, based on circuit-switching, can hardly provide.Carriers have nowadays the option of migrating to new layer-2frame-switched technologies developed ad hoc to support CarrierEthernet. An important question is whether this migration isreally cost effective. This paper deals with the problem of de-

signing a transport network able to support Carrier Ethernet. Wecompare two network models, one based on layer-2 switching andEthernet interfaces, the other based on legacy circuit switchingand SDH interfaces. Minimization of investments for networkinterfaces is carried out for the two models, given the same static-traffic matrix to be supported. Both an ILP formulation and aheuristic method are proposed to solve the design problem. Theresults presented for comparison are obtained by applying theoptimization procedures to a case-study network.

Index Terms Optical networks, network planning, CarrierGrade Ethernet

I. INTRODUCTION

In recent years providers are demanding for a new gen-eration of IP networks able to face the challenges posed

by new services and increasing bandwidth demand. This

main driving force is fostering the current evolution of the

transport-network carriers. The traditional transport infrastruc-

ture, almost-entirely based on large-capacity circuit-switched

trunks, does not seem appropriate any more to deliver packet-

based traffic. SONET/SDH interfaces, ubiquitously deployed

until few years ago, are today matched by the Ethernet-

family interfaces. Thus, the most interesting option available to

carrier operators is the migration from a SONET/SDH-based

infrastructure to the apparently less-expensive and packet-

switching oriented Ethernet counterpart.

The Metro Ethernet Forum (MEF) has defined the services

and requirements of the Carrier Ethernet (CE) [1]. In order to

provide services with their QoS attributes, an Ethernet Virtual

Connection (EVC) [1], a sort of tunnel between two or more

endpoints of a network, has to be established. The delivery

of the end-to-end Ethernet service must be transparent to the

(potentially multiple) transport technologies adopted in the

The work presented in this paper was carried out with the support of theBONE-project (Building the Future Optical Network in Europe), a Networkof Excellence funded by the European Commission through the 7th ICT-Framework Programme.

networks crossed by the EVC. This leaves open the choice

of the technology to the carrier operators.

The currently most common transport solutions to sup-

port CE service are: Ethernet-over-SONET/SDH (EoS) and

IP/MPLS tunneling. Both solutions make use of well-

developed and established switching equipment respectively

operating at layer-1 (circuit-switching digital cross connects)

and at layer-3 (label/packet switching routers).

The activity of standardization of the MEF has spurred ma-

jor standardization organizations, such as IEEE, ITU and IETF,

to develop standards for brand-new network technologies

supporting CE through layer-2 switching. In particular, IEEE

recently standardized Provider Backbone Bridging - Traffic

Engineering (PBB-TE) [2], while ITU-T developed Transport-

MPLS (T-MPLS) [3]. After concerning about the full compati-

bility of T-MPLS with already established IP/MPLS standards,

a liaison between ITU-T and IETF is leading to the definition

of MPLS-Transport Profile (MPLS-TP).

In the next years, we will see which one of the two options,

whether to continue with legacy equipment or to migrate to thenew layer-2 switching concept, will prevail upon the carriers.

Surely, the final choice will be made on the basis of the cost

and the performance of the various solutions.

The main objective of this work is to make a comparison

between the CE transport solution based on Packet-over-SDH

and the upcoming layer-2-switching CE technologies. This

preliminary paper is dedicated to off-line network planning and

optimization on the basis of a static-traffic matrix. In particular,

we will focus on the problem of minimizing the number of

deployed node-interfaces (SDH and Ethernet in the two cases,

respectively). We provide a mathematical formulation of the

network design problem and compare the results given bydifferent optimization algorithms (ILP and heuristics) in a

case-study network. Our intent is to propose new CE network-

design methods and principles. Beside that, we would like to

numerically measure (by simulation) how much the bandwidth

efficiency and multipath capability combine to affect the

choice between Ethernet or SDH technologies.

From the standpoint of this paper, for the assumptions later

reported, the PBB-TE and T-MPLS technologies are treated

as similar. Therefore, we will refer to a more general layer-2

packet-switched (or better frame-switched) CE implementation

instead of explicitly referring to any of such technologies.

978-1-4244-6404-3/10/$26.00 2010 IEEE

This full text paper was peer reviewed at the direction of IEEE Communications Society subject matter experts for publication in the IEEE ICC 2010 proceedings


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This article is structured as follows: after a short description

of prior works (Section II), we discuss in Section III the

issue of planning a CE network in the two SDH and layer-2-

switched implementations, pointing out some assumptions. In

Section IV, we introduce the design and optimization problem

providing a mathematical ILP formulation. In Section V, we

present a simulated-annealing heuristic method. In Section VI,

we show the comparison between the different transport tech-nologies. Section VII draws some conclusions.

II . PREVIOUS WORKS

The main objective of this work is to make a compari-

son between transport technologies used to support CE. The

number of papers currently in literature comparing either the

different CE implementations or legacy transport to them is

rather limited.

Different state of the art papers have been presented, from

[4] presented in 2005 which examines CE technologies, to the

papers based on the CE solutions, such as [5] and [6] or [7].

In June 2006, a technical and economical analysis of PBB

transport technology was presented [8]. A similar analysis

was presented by [9]. A paper concerning the design of a CE

network appeared in IEEE Journal of Lightwave Technology

in January 2008 [10]. The authors studied the problem of

designing reliable and cost-efficient high-rate carrier-grade

Ethernet in a multiline-rate optical network under signal

transmission-range constraints. The same authors presented

other two articles: [11] and [12]. The first one offers an optimal

solution of the transmission-range problem by adopting ILP.

In the second work, the authors propose an algorithm that

provides better performance than the shortest-path one.

In May 2008 [13] proposes a control plane for Carrier Grade

Ethernet networks, taking into account the T-MPLS transporttechnology. The paper [14] describes how to use SDH infras-

tructure to deliver CE services from the providers perspective.

In September 2008, IEEE Communication Magazine dedicated

a special issue to CE technology: in [15], the work done by [7]

is extended; in [16], the attention is focused on the comparison

between PBB-TE and SDH technologies from a qualitative

point of view.

During 2009 several articles regarding Carrier Ethernet

technologies have been published. Among them [17] which

makes a comparison between T-MPLS/MPLS-TP and PBB-TE

from the application point of view and [18] which investigates

the topology of IP layers that minimizes the total transportnetwork cost upon a realistic reference network.

III. NETWORK MODELS AND DESIGN-PROBLEM

DEFINITION

Let us better define the network scenarios we are consider-

ing in this comparative work. From now on, we will refer to

layer-2 packet-switched transport technologies as Packet and

to SDH transport technologies as SDH.

There are several reasons for a possible migration of the

carrier network infrastructure from the SDH to the Packet

technology (Section II). SDH interfaces are regarded as being

more expensive. Moreover, with Packet technology the rate

of flows assigned to each EVC varies with continuity, while

SDH sets-up circuits with fixed bandwidth granularity. We

do not consider here other potential advantages of the Packet

solutions, such as statistical multiplexing, or other QoS related

issues such as delay, delay variation, etc. Such aspects will

be analyzed in future extensions of the paper. Moreover, this

paper considers only point-to-point EVCs (E-Line service),leaving multicast connections (E-Lan and E-Tree service) to

future studies.

Since standardization of the control plane is not yet com-

plete for all the CE technologies, in the Packet case we have

to make some simplifying assumptions on the behavior of

the control of routing operations. In particular, we assume

that all the packets (frames) of an EVC are forwarded as

a single flow between two endpoints on an unique route

through the network, with no bifurcations or merging points.

This assumption complies with the examples provided also in

standards and in [15]. In the SDH case, thanks to the Virtual

Concatenation (VCAT) technology, the traffic of an EVC can

be transported on different Virtual Container (VC) paths which

can follow different routes through the network.

In order to provide a meaningful comparison, we consider

only 10 Gbit/s Ethernet (transmission bit rate of 10312.5

Mbit/s and capacity for PDU payload of 10000 Mbit/s) and

STM-64 (transmission bit rate of 9953.28 Mbit/s and capacity

for PDU payload 9584.64 Mbit/s) interfaces, respectively for

Packet and SDH.

In the Packet case, any value of bandwidth can be reserved

for each EVC on each link of the network. To avoid limitations

in the transmission distances (link lengths), we suppose that

the Ethernet signals generated by the interfaces are trans-

parently carried by Optical Transport Network (OTN) [19].These interfaces allow to extend the reach of transmission

of Ethernet systems without requiring any intermediate en-

capsulation protocol or any change to frame formats or line

encoding (64B/66B). In particular, the so called 10GBASE-R

solution includes the Ethernet frames directly into a slightly

over-clocked version of standard Optical Data Unit (ODU)

container: the ODU-2e container.

In the SDH case, the EVCs have to be accommodated into

the SDH paths. We assume that a quantum of bandwidth

for SDH corresponds to a VC-4 container (payload 149.760

Mbit/s), which thus represents the minimum granularity for

bandwidth reservation in the circuit-switched case. Accordingto a popular and effective EoS implementation, we further

assume that Ethernet frames are encapsulated into the VC-4

containers by the Generic Framing Procedure (GFP) (GFP-F

mapping). As GFP is a very efficient protocol, we will neglect

the limited overhead introduced by frame mapping.

Given all the above assumptions, we can now define the

problem we want to deal with. The network topology (nodes

and links) is given, as well as a set of EVC requests. The

links of the network are optical and contain a variable number

of channels, obtained by multiplying the number of fibers

by the number of wavelengths on each fiber. As nodes are



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assumed to be all opaque (no transparent passthrough allowed,

wavelength conversion and regeneration always available at

each node), the number of wavelengths and fibers exactly used

is irrelevant. The only relevant condition is that the number

of optical channels active on a link in each direction has to

be equal to the number of deployed interfaces. Notice that

actual transmission systems are always symmetrical in the two

propagation directions across a link. Hence, we will have toimpose that the number of interfaces deployed at the two edges

of the same link must be the same.

Each EVC request specifies a source and a destination

among the nodes of the network and a bandwidth to be

reserved for the EVC. EVCs are all unicast and unidirectional

and the traffic matrix is assumed static (permanent connec-

tions). The design occurs offline: nodes have to be equipped

with a suitable number of interfaces, so that enough capacity

exists to accommodate all the EVCs. The function to be

minimized is the total number of interfaces to be deployed. The

output consists of the number and location of the interfaces as

well as the routing of all the EVCs.

In both Packet and SDH cases, we assume that traffic

injected into each EVC is controlled at the source by per-

forming a continuous shaping or policing. The maximum

information rate is strictly enforced, possibly allowing for

short temporary violations to accommodate small-size bursts

of data. The enforced maximum information rate for each EVC

corresponds (after adding frame headers) to the bandwidth

reserved in the network for that EVC. This assumption on

traffic is particularly important for the following reason. One

may wonder if our procedure that minimizes the number of

interfaces is not detrimental for QoS, as it tends to overload the

remaining interfaces. This side effect is avoided if we assume

that statistical multiplexing is not exploited in designing thenetwork in the Packet case, consistently with what previosly

stated. Indeed, this condition is ensured if:

1) each flow loading an EVC is forced to guarantee a

maximum burst-size;

2) an independent portion of buffer (or an independent

buffer) is reserved in each transit node of the network

to each EVC, so that the size of such a buffer is

significatively larger than the corresponding maximum

burst-size.

Under the above hypothesis, a fluid-flow model [20], [21] can

be adopted to analyze the network. According to this model,

the packet loss rate on each EVC (or equivalently the delay)becomes independent of the total load of the links: each EVC

can be loaded up to the capacity reserved in the network

for it, without causing instability. Obviously the advantages

of statistical multiplexing are lost, but this is not a problem.

At the same time, the model allows us to better focus our

Packet vs. SDH comparison just on bandwidth granularity and

interface-related CAPEX.

It should be finally noted that the design procedure pre-

sented in this paper supports EVCs differentiation into two

classes of service: protected and unprotected EVCs. Protected

EVCs requires the reservation of the EVC capacity along a

primary path as well as a secondary one, with the two paths

link-disjoint (only dedicated path protection is considered).

IV. INTEGER LINEAR PROGRAMMING FORMULATION

The formulation we have adopted allows us to apply it to the

two Packet and SDH cases with just a few modifications. Here

follows the description of data, variables, objective function

and constraints: Data:

- G = (V,E): network topology, in which V and E are thesets of nodes and (unidirectional) links, respectively(V=|V|; E=|E|).

- bhs,d: connection request number h of b Mbit/s betweensource node s and destination node d.

- Hs,d: number of requests between s and d, Hs,d = |Hs,d|.- S: set of source nodes.- D: set of destination nodes.- K: set of deployable interfaces per each link.- B: bandwidth of an interface (bandwidth available for

payload).- M: maximum number of interfaces for each link.

Variables:

- Xs,d,hi,j,k

: Xs,d,hi,j,k

= 1 (i = j) if connection request number hfrom s to d is routed across link (i, j) over interfacek, otherwise Xs,d,hi,j,k = 0.

- Ii,j,k: Ii,j,k = 1 (i = j) if the interface k on the link (i, j)has been deployed, otherwise Ii,j,k = 0

Objective Function: route all connection requests deploying theminimum number of bidirectional interfaces.

Minimize :

(i,j)E,kK

Ii,j,k (1)

Constraints:

- Solenoidality constraints, for all s S, d D, and h Hs,d:

jV,kK

Xs,d,hj,i,k =

jV,lK

Xs,d,hi,j,l i = (s, d) (2)

jV,kK

Xs,d,hi,j,k = 1 i S (3)

iV,kK

Xs,d,hi,j,k = 1 j D (4)

- Capacity constraints:

hHs,d

bhi,jXs,d,hi,j,k Ii,j,kB (i, j) V, k K (5)

- Bidirectionality of interfaces constraint:

Ii,j,k = Ij,i,k (i, j) E, k K (6)

Regarding the distinction between Packet and SDH network,we introduce the following rules on the data set:

SDH network:

- B=64 C where C is VC4 capacity.- Each connection request has the same bandwidth as the

payload of a VC4, that is C.- The total number of connection requests is equal to:

Hs,d = bhs,d/C

Packet network:



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- B=10 Gbit/s.

Concerning the protected class of service, we use a dedicatedpath protection algorithm and we introduce a new variable

Ys,d,hi,j,k that is identical to Xs,d,hi,j,k but it refers to the protection

path. Then the capacity constraint becomes:

hHs,d

bhi,j(Xs,d,hi,j,k + Y

s,d,hi,j,k ) Ii,j,kB (i, j) V, k K (7)

The description of Packet and SDH data sets does not differfrom the previous one. Some new constraints must be added tothe unprotected class of service formulation. These constraintshave to be complied for all h Hs,d:

jV,kK

Ys,d,hj,i,k =

jV,kK

Ys,d,hi,j,k i = (s, d) (8)

jV,kK

Ys,d,hi,j,k = 1 i S (9)

iV,kK

Ys,d,hi,j,k = 1 j D (10)

In the end we consider the link-disjointness constraint:

kK

(Xs,d,hi,j,k + Ys,d,hi,j,k ) 1 (i, j) E, h H

s,d(11)

The computational complexity of the ILP in terms of the

number of variables for the unprotected case is equal to

EK[V(V1)H+1]. In the worst case (fully meshed network)it goes as O[V4KH]. For the protected case the number ofvariables is EK[2V(V 1)H+ 1] and, in the worst case, thecomplexity goes as O[2V4KH].

The proof of NP-completeness for the aforementioned prob-

lem () can be given by restriction [22], i.e. by proving that

contains a known NP-complete problem

as a special case.In particular we can restrict the instances of our problem to

a network composed by only two nodes and a link. Under

these conditions our problem corresponds one-to-one to the

bin packing problem, which is NP-hard in the strong sense

[22]. The equivalence (not formally proven here for brevity)

is due to the following properties: the objective function (1),

in which only interfaces are considered as indexes, is the same

of the bin packing problem; constraints (2), (3) and (4) can be

disregarded; capacity constraint (5) has a clear correspondance

to the bin packing capacity constraint; equation (6) only sets

a scaling factor which does not affect the decision problem.

V. HEURISTIC OPTIMIZATION BY SIMULATED ANNEALING

As NP-hard problems typically require long computational

time, we need a heuristic approach to solve realistic-size de-

sign problems. We chose to develop a meta-heuristic approach

based on Simulated Annealing (SA) [23].

We applied it to our case as follows. After a first routing

phase in which all requests are satisfied, an optimization phase

follows, with the purpose of minimizing resource utilization.

The number of deployed Ethernet and SDH interfaces in the

Packet and SDH case is the cost function we are trying to

minimize. The optimization phase uses the Algorithm 1.

Algorithm 1 Simulated Annealing

1) Set the initial temperature (rerouting probability);

2) Save the current state (routing of all connections, de-

ployed interfaces as optimal and current number of

deployed interfaces as minimum cost);

3) Randomly choose a link of the network;

4) Try to reroute all the connection requests passing

through the link: all requests are successfully rerouted: the released

resources (interfaces) can be canceled and a confir-

mation of the positive result is returned;

one or more requests cant be rerouted: the previous

state is restored and a confirmation of the negative

result is returned;

5) Discriminate on the basis of the outcome of the rerouting

routine:

positive result:

- if the number of deployed interfaces decreases

compared to the minimum cost, store the new

state as optimal and keep it for the next SAroutine; go to 6;

- if the number of deployed interfaces increases

compared to the minimum cost but it is under

a threshold, keep the new state for the next SA

routine; go to 6;

- if the number of deployed interfaces increases

compared to the minimum cost and it is over a

threshold, restore the optimal state; go to 6;

negative result: generate a random number between

0 and 1, if this number is lower than the rerouting

probability, add a channel (two interfaces) to all

links, with the exception of the link in which thererouting routine has been attempted;

6) After a fixed number of steps, decrease the temperature

(rerouting probability);

7) Repeat the steps from 3 to 6 until the temperature

(rerouting probability) is below a fixed threshold.

V I. LAYER-2 SWITCHING VERSUS SD H

We now discuss the comparison between layer-2 switching

and SDH in terms of number of deployed interfaces (CAPEX),

which is intended to be the final goal of the paper. On this

account it should be noted that more than providing a response

on which is the most cost effective solution, we intend

to elaborate a methodology of comparison to quantify the

difference between the two technologies in terms of number

of deployed interfaces, trying to identify network and traffic

conditions that make one solution more suitable than the other.

Given the assumptions described so far on the defined

network models and scenarios, two main phenomena affect the

number of deployed interfaces: (a) granularity; (b) multipath.

SDH suffers a granularity impairment compared to layer-2

switching because: i) the bandwidth in SDH can be assigned



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to connections in chunks of VC-4 capacity; ii) the bit rate ofan SDH interface (9953.28 Mbit/s) is slightly lower than the

rate of a 10GE interface (10312.5 Mbit/s). It is easy to realize

that the global effect of the granularity impairment decreases

as the overall volume of traffic and as the average bandwidth

required per traffic flow get large. Viceversa, granularity effect

is strengthened when the average path-length (in number of

hops) increases.On the other hand, the layer-2 switching solution suffers a

multipath impairment compared to SDH. This is due to the

capability of SDH, given by VCAT, of slicing a single flow

on multiple paths across the network, creating a load-sharing

effect that is expected to improve performance. However, it

should be considered that the multipath effect can be actually

appreciated in case two or more paths with disjoint interfaces

exist and the amount of available bandwidth on the minimum

cost path is less than the requested one; this means that con-

nection requests are forced to pass through different disjoint

paths. Thus, low nodal degree and small number of available

resources are expected to reduce the impact of the multipath

impairment, especially when the requested bandwidth per

connection is low.

The neat result of the combination of granularity and

multipath is not obvious. Let us consider the simple case in

which the requested bandwidth is equal for each connection

and let us focus a single network node n. The number ofoutgoing interfaces needed by n in the Packet and SDH casebe OIP and OIS , respectively. We have

OIP = r/BP/b (12)

OIS = (b/CV C4 r CVC4)/BS (13)

where r is the number of connection requests of bandwidth barriving at the node n; CVC4, BP, BS , are the bandwidths ofa VC4 container, a Packet and an SDH interface, respectively.

It should be noted that r accounts for connection requests forwhich the considered node is either the source node or a transit

node.

In figure 1 we show the two curves representing OIP andOIS of n in the simple theoretical case of a network of twonodes n and m and one link ln,m. In such case n is sourceof all the r connection requests (n can not be transit node)and thus r can be assigned arbitrarily (r = 15 in the figure).The two curves are represented as functions of the normalized

bandwidth = b/BP. The vertical axes is also normalizedto the maximum number of output interfaces, which is givenby SDH when is equal to 1 (since BP > BS). It canbe observed that for low values of the two technologieshave similar trends; sometimes SDH needs more interfaces,

because of the granularity impairment. Around intermediate

values of this trend changes, and for 0.5 the SDHtechnology is noticeably cheaper than Packet, because of the

the multipath impairment prevailing. For rational values of

, Packet always performs better than SDH because it fillsexactly the available payload on the interface and the multipath

effect becomes useless, leaving the granularity impairment to

0 0.1 0.2 0.3 0.4 0.50

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Normalized Requested Bandwidth ( )

Normalizednumberofou

tputinterfacespernode

PACKET

SDH

Fig. 1. Number of output interfaces per node needed to setup connectionswith equal requested bandwidth in a point-to-point link.

prevail. We have verified that the same behavior holds for non

degenerative networks, this suggests that estimating a CAPEX

comparison between SDH and Packet by the simple eqs. 12

and 13 is possible. Moreover, {r,b,CV C4, BP, BS} are themain parameters an operator should consider to decide whether

to invest in SDH or Packet interface, independently of the

network topology and complexity.

We finally show the comparison between the SA heuristic

and the exact ILP approach in the optimization of the number

of interfaces for static traffic and a realistic network. The

comparison has been carried out for the two SDH and Packet

technologies and for both classes of service (protected andunprotected). The chosen network is the Pan-European Re-

search Network Geant2* [24] (shown in figure 2). The results

SE

IE

UKNL

PL

CZFR

BEDE

CHXX

AT

SI HR

HU

ES IT

GR

Fig. 2. Geant2* network topology.

are depicted in figure 3. The plotted graphs show that the

difference between the results obtained by SA and ILP is

always beyond 10%. The static traffic is built starting from

a matrix (taken from the project MUPBED [24]) representing



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1e+1

1e+2

1e+3

0 5 10 15 20 25 30

ILP - PACKET - NO PROTSA - PACK - NO PROTILP - SDH - NO PROTSA - SDH - NO PROTILP - PACK - PROTSA - PACK - PROTILP - SDH - PROTSA - SDH - PROT

NumberofDeploy

edInterfaces

Traffic Scale Factor

Fig. 3. Number of deployed interfaces in Geant2* network.

the estimation of actual traffic volumes between the nodes of

the network. The total traffic volume has been varied over a

limited range to ensure ILP convergence within a reasonable

computational time. ILP has been performed on a standard pc

using CPLEX software. As expected the computational time

for SA is on average much lower (a few hours) than for ILP

(a few days).

The interfaces deployed in the Packet network are always

less than those in the SDH one, not only because of the

granularity constraint which affects SDH circuits, but also

because the multipath effect is nearly absent. In fact at thehighest traffic scale factor, the average requested bandwidth is

925 Mbit/s, which in most cases is too low to conveniently

exploit VCAT multiple paths. Moreover, the Geant2* topology

is characterized by a low average nodal degree, thus making

few different paths available for VCAT.

VII. CONCLUDING REMARKS

This paper deals with the problem of optimizing networks

able to support Carrier Ethernet connections. The purpose is

to evaluate the advantages of flexible access to bandwidth,

deriving from the adoption of layer-2 switching technologies

(such as PBB-TE and T-MPLS), against the disadvantages of

the fixed bandwidth granularity of SDH networks. We have

presented an integer linear programming formulation of the

problem of minimizing the number of interfaces deployed in

the network to setup a given static connection-request matrix,

and proposed a less computationally-hard heuristic based on

simulated annealing.

This preliminary study allowed us to identify a set of

fundamental parameters to evaluate the pros and cons of mi-

grating from legacy technologies to newfangled ones. It should

be finally commented that our study leads to comparisons

based solely on the number of interfaces, but a 10 Gigabit

Ethernet interface is reputed to be less expensive than an SDH

interface. Hence, the advantages of the Packet in terms of

monetary CAPEX value are probably more remarkable than

what predicted here.

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