Provisioning Methods for Bit-Rate-Differentiated Services in Hybrid ...

Photonic Network Communications, 7:1, 59±76, 2004 # 2004 Kluwer Academic Publishers. Manufactured in The Netherlands.

Provisioning Methods for Bit-Rate-Differentiated Services in Hybrid Optical Networks Maher Ali Alcatel Research and Innovation, 3400 West Plano Parkway, M/S CTO2, Plano, TX 75075, U.S.A. E-mail: [email protected]

Denis Penninckx Alcatel Research and Innovation, Route de Nozay F-91461, Marcoussis Cedex, France E-mail: [email protected] Received June 12, 2003; Revised and Accepted July 25, 2003

Abstract. This paper addresses the problem of routing and wavelength assignment of bit-rate-differentiated optical services in a hybrid network. Hybrid optical networks are composed of resources, such as ®ber links and photonic/electronic switches, that vary in their capabilities and transmission qualities. These networks are also responsible for the realization of optical services with varying quality-of-service (QoS) guarantees. In such networks, it is required to have a cost-effective assignment of the optical and electronic resources to these services in order to maximize the revenue of the network operator. This paper deals with optical services that are de®ned according to their tolerance to transmission impairments. We ®rst divide the provisioning problem into two phases: (1) routing and (2) wavelength assignment and regeneration reservation. In the routing phase, a set of k-routes are generated to select from in the second phase, where each route optimizes a speci®c aspect of the problem (e.g., number of hops, maximum accumulated noise, etc.). The second phase, using the information about the resources along each route, attempts at ®nding the best wavelength allocation on that route such that the signal quality meets the service-level agreement (SLA). The second phase also uses the minimum number of regenerator ports on intermediate nodes for the purpose of wavelength translation and signal clean-up. Comparisons of the above scheme with a probing-based method, reveal substantial enhancements to the blocking performance with a maximum running time increase of 60%. In addition, the use of multiple routes provides higher reduction in the blocking probability over single-routing schemes. Moreover, the proposed, non-pessimistic, provisioning approach has a major impact on reducing the regeneration budget of the network. Keywords: optical networking, transmission impairments, routing and wavelength assignment, optical quality-of-service (QoS)

1

Introduction

The recon®gurable optical mesh networking model is believed to be the answer to the demand for highbandwidth and the emergence of differentiated optical services. In such a network, the control-plane/network-management software is responsible for the dynamic assignment of optical and electronic resources to differentiated optical services. The costeffectiveness of recon®gurable optical networks depends, to a large extent, on the effective assignment of optical resources to these optical services. An optical network is referred to as hybrid if the optical/ electronic resources such as the ®ber links, photonic switches, and optical-electronic-optical (OEO) regenerator devices vary in their characteristics in the

network. It is becoming clear that the future optical network will be a hybrid one. Not only that ®ber links vary in their optical qualities, may have a limit on the maximum bit-rate, are protocol transparent (i.e., no inline regeneration), etc., but also optical services vary in their requirements [1,2]. For example, a 2.5 Gb/s connection can tolerate more to be routed on low-quality ®bers than, for example, a 10 Gb/s circuit. One of the main objectives of the provisioning software is the dynamic mapping of optical resources to the optical services such that the total revenue of the network is maximized and service-level agreements (SLAs) are met. Various approaches exist in the literature for the dynamic provisioning of lightpaths. These schemes can be classi®ed as either centralized or distributed. In the centralized approach, a central

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M. Ali, D. Penninckx/Provisioning Methods For Bit-Rate-Differentiated Services

entity is responsible for the establishment and the termination of optical services. This entity keeps track of the network resources and does allocate the resources to optical services on-demand. This approach provides the most ef®cient utilization of the network resources. However, it goes in opposite direction to the Internet philosophy that favors scalable and robust schemes. The second approach is distributed provisioning. In this scheme, all nodes are treated as being equal in their provisioning responsibility and there does not exist a centralized entity. The availability of the network resources are distributed through the interiorgateway protocol (IGP) such as the open-shortest path ®rst protocol with traf®c engineering extensions (OSPF-TE). The ingress node utilizes this routing information and use it to calculate the path to the egress node. This approach is more reliable and robust than the centralized scheme. However, it suffers from two main problems. First, the ef®ciency of the path computation; hence the blocking performance and resource utilization, is lower than the centralized scheme. This is due to the fact that not all link information are up-to-date as time is needed for linkstate convergence. The second problem is a scalability issue due to the spectral information. Spectral information related to wavelengths, that can become very large in size, cannot be distributed in OSPF-TE; otherwise the distribution of this information becomes the bottleneck in the control channel. Recently, there has been some activities concentrating on addressing the impact of transmission impairments on the routing process and the ensuing network optimization [3±5]. Two of the most important physical impairments limiting the maximum transparent segment in optical networks are polarization-mode dispersion (PMD) and ampli®ed spontaneous emission (ASE) noise [6]. The interesting problem that arises due to transmission impairments is the heterogeneity of the ®ber links and the tolerance of optical services to physical impairments. Old ®ber links can in¯ict more impairments. These impairments have the side effects of increasing the regeneration budget as well as the overall BER. Such old ®bers can have, for example, an average p PMD coef®cient ranging from 2 to 0:4 ps= km. New and improved ®bers lessen, to some extent, the PMDp effect and have PMD  coef®cient around 0:1 ps= km. Moreover, old ®bers often exhibit higher loss yielding a lower optical

signal-to-noise ratio (OSNR). The non-homogeneous optical resources mandate that the provisioning software takes the transmission quality of the optical resources into consideration during the routing phase. This enables network optimization taking into account the cost of regenerators, as indicated in Ali et al. [3] where substantial savings were demonstrated. One can envision different classes of traf®c (e.g., different bit-rates) offered in a wavelength-routed network. These classes can vary in their minimum signal quality requirement, survivability guarantees, etc. The optical network must be able to differentiate between these classes of traf®c allowing for proper connection admission as well as better utilization of the heterogeneous optical resources. From the quantitative measures perspective, different classes will have different demands in terms of signal quality and hence will be routed differentlyÐhigher-class traf®c will be routed through links with better quality. In this paper, we focus on the problem of routing and wavelength assignment while satisfying the bitrate requirements of the service. The provisioning goal is the minimization of both the number of reserved OEO regenerators (needed for signal cleanup and wavelength-translation) as well as the blocking probability. The algorithms and performance evaluation presented in this paper do not assume any particular provisioning approach; thus they are applicable to both distributed and centralized schemes. This paper is organized as follows. In Section 2, the main physical impairments are discussed and optical services are de®ned. In Section 3, the hybrid network and node architectures, along with the proposed provisioning scheme are presented. In Section 4, the spectral routing problem is formulated and a solution is proposed. In Section 5, performance analysis of the ideas discussed in this paper are presented. Finally, we give the summary of the paper in Section 6.

2

Physical Impairments and Optical Services

In the following, we discuss two of the main impairments (as identi®ed in Strand et al. [6]) in an optical network that limit the maximum transparent segment of a lightpath: OSNR degradation and PMD. After that, we de®ne two optical services based on these impairments.

M. Ali, D. Penninckx/Provisioning Methods For Bit-Rate-Differentiated Services

2.1 Optical Signal-to-Noise Ratio (OSNR) Although the channels operating in the low-loss region of the ®ber bandwidth incur a relatively small loss (e.g., 0.22 dB/km on a ®ber, and 4 dB for a WDM demultiplexor), signal ampli®cation is needed for long-haul networks. These losses can be compensated by in-line ampli®ers such as erbiumdoped ®ber ampli®ers (EDFAs). EDFAs, however, have the negative side effect of introducing ampli®ed spontaneous emission (ASE) noise. This noise travels with the signal and is accumulated along the path; thus contributing to the deterioration of the OSNR. Consider an ampli®er of net linear gain G and input insertion loss C1 . For an input signal channel of power Pin having an input signal-to-noise ratio osnrin , the ®nal signal-to-noise ratio osnrout at the output of the ampli®er is given by: 1 1 1 ˆ ‡ ; osnrout osnrin osnramp

…1†

where osnramp is the amount of deterioration of the input signal-to-noise ratio osnrin due to the ampli®er, and is given by: osnramp ˆ

Pin ; hs Bref F

…2†

where h is Planck's constant, s is the optical central frequency of the signal, Bref is the reference optical bandwidth of analysis centered around s and in which the signal-to-noise ratio is measured, and F is the noise ®gure of the ampli®er and is given by 2nsp =C1 , where nsp is the spontaneous emission coef®cient. In general, the osnrout at the end of a k-stage EDFAs is given by: ! k X 1 1 1 ˆ ‡ ; …3† osnrout osnrin i ˆ 1 osnramp…i† where osnramp…i† is the signal-to-noise ratio deterioration due to the i-th ampli®er. 2.2 Polarization-Mode Dispersion (PMD) PMD occurs due to the imperfect construction of ®ber links. This imperfection gives rise to having the two polarization modes of the pulse to have different propagation constants; thus leading to pulse spreading. For the signal to be detected at the receiver within acceptable bit-error rate (BER), the timeaveraged DGD between two orthogonal states of

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polarizations, Dt, must be less than a fraction of the bit-rate [7]. Equation (4) adapted from Strand et al. [6], provides such a constraint: r  X 2 DPMD …l† 6Length…l†  a; Bandwidth6 l [ Path

…4† where DPMD …l† is the PMD parameter on Fiber l and a typical value for a is 0.1. It is worth noting that PMD is not a noise, and does independently affect the maximum transparent segment. 2.3 Optical Services We make use of two services: 2.5 Gb/s and 10 Gb/s. In this section, we would like to derive the limits on the OSNR for each service. Assuming Gaussian statistics for the noise, the BER can be found using the following expression:   1 Q BER ˆ er fc p : …5† 2 2 Where Q is the quality factor de®ned by the difference of the mean values of the 1 and 0 levels divided by the sum of their standard deviations. Let Bref be the reference bandwidth within which the OSNR is computed, traditionally equal to 0.1 nm or 12.5 GHz at 1550 nm, and let Be be the electrical bandwidth of the receiver. It can be shown that, with a good approximation, the above expression can be written as Penninckx and Audouin [8]: p s! 1 Q0 OSNR Bref p BER ˆ er fc ; …6† 2 Be 2 where Q0 is the eye aperture for optically ampli®ed systems. Q0 is equal to 0 when the eye is closed, to 0.75 for an NRZ signal with 13 dB extinction ratio and often close to 0.6 after propagation when the shape of the eye is slightly degraded. For a BER of 1:6610 4 , before forward-error-correction (FEC), we have Q ˆ 3:6. Let Be ˆ 1:875 GHz for 2.5 Gb/s and equal to 7.5 GHz for 10 Gb/s. Also, assuming Bref ˆ 12:5 GHz and Q0 ˆ 0:6, we get the requirements on the minimum OSNR for the 2.5 Gb/s and 10 Gb/s services to be 10.4 dB and 16.4 dB (10.8 and 43.2 in linear scale), respectively. The maximum PMD accumulation used in the simulation is 40 and 11 ps for 2.5 Gb/s and 10 Gb/s, respectively.

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The Hybrid Optical Network

The hybrid optical network is composed of heterogeneous ®ber links, photonic switches, and OEO devices. It is also responsible for the realization of differentiated optical services. In this section, we ®rst present the network node architecture used in this paper. Next, we discuss the proposed two-phase provisioning approach. 3.1 Hybrid Node Architecture The network node can be used to provide one or more of the following functionalities: 1. Optical Bypass. An input signal coming on ®ber I and wavelength lk and destined to output ®ber O and wavelength lk that can tolerate the signal degradation on ®ber O, should be able to bypass regeneration and transparently be multiplexed on port O. 2. Signal Restoration. A degraded signal that cannot go beyond the current intermediate hop without regeneration should be able to request a regeneration port and continue on the same or some other new wavelength. 3. Wavelength Translation. A signal that is coming on a given lambda lk , where lk is occupied on the output ®ber, should be able to request a wavelength translation function at the intermediate node. A regenerator can serve for both signal restoration and wavelength translation at the same time. Fig. 1 shows the architecture of the network node considered in this paper. It consists of two boxes: (1) the hierarchical photonic switch that is capable of providing wavelength, band, and ®ber switching, and (2) the shared regenerator bank providing signal regeneration and wavelength translation functionalities. Both the photonic and electronic boxes are controlled using the control-plane. It is worth noting that the functionalities of the network nodes do not only differ from node to node, but also can vary (by time) at a given node. For example, a wavelength chosen at an intermediate node may not be available to receive regeneration at that node due to, for example, the switching state of that node (e.g., the wavelength is grouped with others into a waveband which cannot be demultiplexed [9,10]).

Fig. 1. The hybrid network node used in this paper. It consists of a hierarchical photonic switch and a shared electronic regeneration bank.

3.2 Overall Provisioning Approach Using the information about the optical and electronic resources in the network, we would like to ®nd a feasible lightpaths from the ingress to the egress that is consistent with the bit-rate requirements while minimizing the number of regenerators used. In the following, we present a two-phase approach for this problem. Phase 1. Finding k-routes. In this phase, k-routes are found from the ingress to the egress. Each route is found as follows. First, an auxiliary graph is constructed representing the current connectivity of the network. A physical link is added to this graph if and only if (iff ): (1) at least one wavelength is free on the link and (2) the link is capable of carrying the

M. Ali, D. Penninckx/Provisioning Methods For Bit-Rate-Differentiated Services

required service (e.g., its PMD accumulation is below the PMD threshold for the service). After constructing the graph, each link is labeled with a number. This number represents the objective we wish to minimize on the route. For example, a label of 1 on all nodes is used in ®nding a route with minimum number of hops. After labeling the links, Dijkstra's shortest path is used to ®nd the route from ingress to egress according to the above metric. Phase 2. Wavelength Assignment and Regeneration Reservation (WARR). In this phase, each route along with the resource availability on its nodes and links, are used to ®nd the best wavelength assignment on the links which minimizes the number of regenerators needed for wavelength translation and signal cleanup. In the next two sections, we address the important problem of wavelength assignment and regenerator reservation (WARR). Note that the solution of the WARR problem can be done at either (1) the ingress node, using the distributed information, (2) in the centralized management system entity, (3) in a distributed hop-by-hop manner, or (4) at the egress node similar to the approach proposed in Ganguly and Modiana [11], where the authors only address the simple all-optical (i.e., wavelength-continuous) case.

above the threshold speci®ed in (4) and the total number of regenerators used for this connection at intermediate nodes is minimized. 4.2 Mathematical Formulation of the WARR Problem Given the information on the set of routes received, for example at the egress node, the task is to select the best route with respect to the number of regenerators allocated. In the following, we present an optimal solution approach for ®nding the wavelength assignment and regeneration sites given the route and resource availability on nodes and ®bers constituting this route. This solution is given on the form of an ILP. The objective is to minimize the number of regenerators used for wavelength translation and/or signal regeneration.

4.2.1 Notation and Variables The following notation and variables are used: *

*

* *

4

The WARR Problem *

In this section, we introduce the WARR problem. First, we provide the problem de®nition. Second, we present a mathematical formulation of the problem in the form of an integer-linear program (ILP). Next, a simple heuristic is discussed. Finally, a new algorithmic realization of the mathematical formulation is presented. 4.1 Problem De®nition De®nition: WARR Problem. Given (1) a spatial route represented by its ®ber links, (2) the spectral information (wavelength availability, quality, etc.) on each ®ber, (3) the availability of regeneration at each intermediate node of the route, and (4) the transmission quality required at the destination (e.g., maximum PMD, minimum OSNR, etc.). The question is how to ®nd the wavelength assignment on the route such that the signal is received at the destination

63

*

*

*

*

*

…s; d†. Connection request from ingress node s to egress node d. W. The set of wavelengths available on a ®ber link. K. Set of nodes on the route. Avail…w; l†. A constant equals to 1 if and only if (iff ) wavelength w is free on ®ber l. Regen…a; w†. A constant that is equal to 1 iff wavelength w can be regenerated at crossconnect a. Xlw . A binary variable that is equal to 1 iff the connection request is routed using wavelength w on ®ber l. gw;t l; f . A binary variable that is equal to 1 iff a regenerator is used in connecting ®bers l and f due to the conversion from wavelength w on ®ber l to wavelength t on ®ber f. Ca . A binary variable that is equal to 1 iff a regenerator is used in connecting ®ber l ˆ …b; a† and ®ber f ˆ …a; c†. MAXpmd . A constant indicating the maximum PMD tolerated at any point along the route of the connection. PMDa . The total accumulation of PMD from the last regenerator on the route (or from the source s) to node a.

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M. Ali, D. Penninckx/Provisioning Methods For Bit-Rate-Differentiated Services *

*

*

*

*

*

*

*

PMDrev a . The value of PMD at node a that is either propagated or is fresh after the installation of a regenerator at node a. PMDl . A constant indicating the PMD value on ®ber l. 1 MAXosnr . A constant indicating the maximum 1=OSNR tolerated at any point along the route of the connection. OSNRa 1 . The ratio of the total accumulation of optical noise to the signal from the last regenerator on the route (or from the source s) to node a. 1 OSNRa;rev . The value of 1=OSNR at node a that is either propagated or is fresh after the installation of a regenerator at node a. OSNRwl . A constant indicating the OSNR value on ®ber l and wavelength w. Taw . A binary variable that equals to 1 if a regenerator is installed at node a due to the violation of the transmission impairments on wavelength w. Ra . A binary variable that equals to 1 iff a regenerator is installed at node a due to either the violation of the transmission impairments or wavelength translation, or both.

*

w[W

*

*

*

For any two consecutive ®bers l and f on route, the ¯ow-constraint is given by: X X Xlw ˆ Xft : …7† w[W

t[W

A wavelength can be used if it is available on the ®ber. …9†

Consider two consecutive ®bers l ˆ …b; a† and f ˆ …a; c†, and two different wavelengths w and t, the use of a regenerator for wavelength translation between the two wavelengths is captured by the following: w t gw;t l; f ˆ ROUND1…Xl ; Xf †:

*

…10†

The wavelength translation from wavelength w to wavelength t in the above constraint can only occur if such conversion is available at crossconnect a. gw;t l; f  Regen…a; w†:

4.2.2 Helping Functions The following two functions are used internally as rounding functions.

4.2.3 Constraints and Objective Function In the following, we list the constraints and objective function of the problem. The constraints of the problem are as follows:

w[W

Xlw  Avail…w; l†:

*

1. BINARY ROUND1…a; b† ˆ 1=2…a ‡ b† ‡ e, where 0:5  e  0. 2. BINARY ROUND2…a; b† ˆ 1=2…a ‡ b† ‡ D, where 0  D  0:5.

The connection is transmitted and received on any wavelength. Let l and f be the links from ingress node s and egress node d to their immediate switch, respectively, we have: X X Xlw ˆ Xfw ˆ 1: …8†

…11†

Consider two consecutive ®bers l ˆ …b; a† and f ˆ …a; c†, a regenerator is used for wavelength translation between l and f if a wavelength interchange is used between any two different wavelengths. X X w;t Ca ˆ gl; f w 6ˆ t: …12† w[W t[W

*

A regenerator request at Node a can come from either transmission problem or wavelength translation or both. ! X Taw : Ra ˆ ROUND2 Ca ; …13† w[W

*

Regeneration of wavelength w at cross-connect a can be used only in the case where wavelength w is used on ®ber l ˆ …b; a† and the regenerator at cross-connect a is available. Taw  Xlw ;

…14†

Taw

…15†

 Regen…a; w†:

M. Ali, D. Penninckx/Provisioning Methods For Bit-Rate-Differentiated Services *

The PMD value at a node a is found as the sum of the PMD value at the previous node b and the PMD value of the link between the two nodes. Let l ˆ …b; a†, we have: PMDa ˆ PMDrev b ‡ PMDl : 1

Similarly, the OSNR OSNRa

1

ˆ

is given by:

1 OSNRb;rev

‡

X

 1 w 6Xl : OSNRwl

w[W *

…17†

The PMD and the OSNR 1 values cannot exceed their threshold values.  MAXpmd ;

PMDa OSNRa *

…16†

1

 MAX

osnr

…18† 1

:

…19†

The PMD value propagated from a node a can be decreased, provided a regenerator is present at node a. Informally, this can written as:  0; Ra ˆ 1 rev PMDa ˆ …20† PMDa ; Ra ˆ 0. Formally, the above can be written in a linear form as follows. Let a be a relatively large number. We have: PMDrev a ˆ PMDa

aRa ‡ gpmd a : 1

Similarly for the OSNR 1 OSNRa;rev ˆ OSNRa

1

…21†

value: 1

Ra ‡ gosnr : a …22†

*

The variables are classi®ed as follows: w w Ca ; gw;t l;f ; Ta ; Ra ; Xl [ f0; 1g; pmd osnr PMDa ; PMDrev a ; ga ; ga 1 OSNRa 1 ; OSNRa;rev 

1

…23†  0;

1 : 1000

…24†

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4.3 A Simple Probing-Based Scheme A simple solution for the WARR problem can be based on the probing provisioning approach discussed in Yuan et al. [12], Shami et al. [13], Kejie et al. [14], and Shami et al. [15]. The probing method solves the WARR problem hop-by-hop without backtracking. The algorithm starts by the set of available wavelengths at the ingress node and initializes the signal quality values for all available wavelengths to their default values (0 ps for PMD and 1000 (30 dB) for OSNR). At each intermediate node, the set of wavelengths is replaced by the intersection (AND function) of available wavelengths on the output interface of that node and the current set of wavelengths accumulated so far. The signal quality of each channel is updated due to impairments on the input ®ber of that node. At any intermediate node, if the set of wavelengths becomes empty, the node attempts at wavelength translation from any input wavelength to any wavelength available at the output interface. If no such translation function can be achieved, the connection is blocked. Similar procedure is followed if the signal quality is degraded and a fresh signal is needed through regeneration. If a nonempty set of wavelengths is received at the egress node, one (arbitrary) wavelength is used for reception. Clearly, this scheme is suboptimal in the case of hybrid networks. A network which employs sparse regeneration and/or sparse conversion (i.e., some nodes are not equipped with regenerators/converters), can have a sub-optimal blocking performance using this scheme. To illustrate the weaknesses of this method, consider the route in Fig. 2, where only node 1 can provide wavelength translation. Also, for simplicity, let us assume that signal impairments are not considered. The probing starts with the set fl1 ; l2 ; l3 g. At node 1, the wavelength set is update by intersecting it

…25†

Note that we assume that the OSNR at the output of a regenerator is not in®nity, but rather a large number (1000 or 30 dB). The objective function is to minimize the total number of regenerators allocated on the intermediate nodes of the route. Let Y ˆ K fs; dg, we have: X Minimize Ra …26† a[Y

Fig. 2. A route example with available wavelengths on each of its links. Only node 1 can perform wavelength translation.

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with the set of available wavelengths on the next link which leads to fl2 g. At node 2, the set becomes empty and the connection is rejected since there are no regenerators available at node 2 that can translate from l2 to any wavelength in fl5 ; l7 ; l8 g. In this example, a wavelength translation at Node 1 from one of the wavelength in fl1 ; l2 ; l3 g to Wavelength l5 successfully allows the connection to be established. Since the scheme visits all the nodes and at each node the full set of wavelengths are processed, the time complexity of the probing method is O…jKjjWj†. The simplicity of this scheme in general, and its optimality in non-hybrid networks, however, makes it popular. 4.4 Algorithmic Solution Approach for the WARR Problem In this section, we present a new algorithmic approach for solving the WARR problem. The algorithm (shown in Fig. 3) can be used in the routing process at, for example, the egress node. It uses two functions shown in Figs 16 and 17 in the Appendix. The algorithm, WaveAndRegenAssignment takes, as input, the ingress and egress nodes and the spatial route. It returns the set of wavelengths on each segment and the location of the regenerators to be reserved on the route. If no feasible routing exists, it returns NULL. The algorithm aims at ®nding the minimum number of transparent segments from the ingress to the egress. It achieves that by utilizing the ScanSegment function shown in Fig. 16 in the appendix. ScanSegment ®nds the wavelength that provides the maximum wavelength-continuity and can be regenerated at the node

Fig. 3. An algorithm that ®nds the minimum number of regenerators needed to solve the WARR problem.

where it is interrupted. It does so by considering not only the availability of the wavelength on all ®bers of the segment, but also the quality of the optical signal requested. After ®nding the maximum route length for each available wavelength on the segment, the wavelength with the longest route is reported using the Function ScanBestPoint in Fig. 17 in the appendix. This process is repeated until the egress node is reached or the connection is blocked. In the following, we show that the proposed algorithm is optimal and runs in polynomial time. Theorem 1: The above algorithm ®nds the optimal solution for the WARR problem in polynomial time. Proof: Observe that the optimal solution for the WARR problem is that which minimizes the number of transparent segments, where these segments are interconnected via OEO devices. Let us consider the optimal ®rst segment. This segment uses some wavelength li starting from the ingress node and ending at some intermediate node I such that: (1) Wavelength li is either not available on the output link of Node I or will be degraded beyond recognition at some point on the output link of node I before reaching the ®rst downstream node from node I, and (2) Wavelength li can be regenerated at node I to any available channel on the output link of node I. Since Function ScanSegment exhaustively searches all such wavelengths, such an optimal segment can be found. Now, the fact that the OEO architecture we assume in this paper is tunable-input/tunable-output, allows for the guarantee of the optimality of the concatenation of individually optimal segments. Hence the overall route is optimal. It is easy to see that the time complexity of WHILE loop in Fig. 3 is O…jKj†. Inside the loop, the Function ScanSegment is run each time. ScanSegment has two main loops. The ®rst one is a double loop and has running time complexity of O…jKjjWj†. The second loop calls the function ScanBestPoint O…jWj† times and has time complexity of O…jKjjWj†. Hence, a O…jKj2 jWj†, albeit loose, upper-bound on the time complexity, provides the polynomial time guarantee. & In the next section, we demonstrate, through simulations, that the substantial reduction in the blocking probability using the optimal solution, can be achieved with relatively small percentage of

M. Ali, D. Penninckx/Provisioning Methods For Bit-Rate-Differentiated Services

increase in computation time compared with the suboptimal probe-based scheme. 5

Performance Study

In this section, we study the performance of the ideas and algorithms presented in this paper. First, we discuss the major control parameters in the simulation. Next, we list the evaluation metrics used. Third, the network topology and its random con®gurations (in terms of link physical quality) are presented. Finally, the results are discussed. 5.1 Control Parameters The control parameters of the numerical study are as follows: 1. Load. The load is used to assign channel occupancy. Let li be a wavelength on link l. Let x be the load, 0  x  1. A uniform random number, t, is drawn from ‰0; 1Š. Wavelength li on link l is ¯agged as being occupied if t is less than or equal to x. This process is repeated for all wavelengths and all links in the network. 2. Regenerator Availability. The regenerator availability is de®ned as the probability of a free regenerator at node n for a given wavelength. The regenerator availability at a given node is randomly and uniformly assigned using this probability. 3. Set of Spatial Routes. The set of spatial routes used in this study is hop-count, impairment. The ®rst route is that which minimizes the number of links from ingress to egress. The other route is that which minimizes the total degradation of signal. Two sources of impairments are used in this paper: PMD and noise. The PMD contribution for pa given  Link l is de®ned as …PMDl 6 Length…l††=MAXpmd . The Noise contribution for a given link is de®ned as the minimum noise accumulated on an available wavelength on that link and given by: 1 …1=OSNRl †=MAXosnr . The impairment metric that was used is simply the sum of the PMD and the noise contributions giving the same weight to PMD and OSNR. 5.2 Evaluation Metrics The evaluation metrics used in this study are:

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1. Blocking Probability. The blocking probability is de®ned as the number of connections that were not established to the total number of connections requested. The total number of connections used in each evaluation is 500. The source and destination of each connection are randomly and uniformly chosen from the set of nodes. 2. Average Number of Regenerators per Path. The average number of regenerators per path is de®ned the total number of regenerators used in establishing the successfully routed connections divided by the total number of these connections. 5.3 Network Topology and Con®guration Throughout this paper, we make use of the network topology shown in Fig. 4. This nation-wide network is composed of 79 nodes and 99 bidirectional ®bers. Each edge represents two unidirectional ®bers in opposite direction. The number of wavelengths on each ®ber is 32. For each of the 198 unidirectional ®bers, we have randomly drawn PMD and OSNR values by taking into account realistic physical assumption as shown below. We have considered three networks having respectively 50%, 70% and 90% of ``new'' ®bers. The ``new'' p ®ber  is characterized by a better PMD (0:1 ps= km instead of p 0:4 ps= km) and a lower loss (from 0.22 to 0.26 dB/km instead of 0.24 to 0.28 dB/km than the older ones). For each percentage of ``new'' ®bers, a mixture of two transmission systems was considered: long-haul (LH) and ultra-long-haul (ULH) systems. We assume that the features of the transmitters and receivers in this transparent network are the same for both LH and ULH. Hence, regardless of the transmitter, a connection can be routed on any link and a connection may go through a ®ber equipped with ULH and then through a ®ber equipped with LH or vice-versa without need to regenerate the signal inbetween. ULH systems are installed for a link if and only if the link is longer than 350 km and if the ®ber is ``new'' and hence exhibits a low PMD and a low loss. Only 30% of the links are longer than 350 km in our topology. Thus, the average proportion of ULH is equal to 30% of the percentage of ``new'' ®bers. The spacing between two consecutive ampli®ers was randomly drawn from 60 km to 110 km with a ¯at distribution. ULH systems differ from LH systems in the use of Raman ampli®cation (which results in a

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M. Ali, D. Penninckx/Provisioning Methods For Bit-Rate-Differentiated Services

Fig. 4. Optical network topology used in this study. Network is composed of 79 nodes and 198 unidirectional ®bers.

lower OSNR degradation) and automatic gain equalizers (AGEs), which results in reduction of power ¯uctuation from channel to channel. Parameters for LH and ULH are summarized in Table 1. For each percentage of ``new'' ®bers (50%, 70% or 90%), simulations were performed 10 times with different random generations of the allocation of the ``new'' and ``old'' ®bers and of the OSNRs of each of the 32 channels. Table 2 shows the typical OSNR obtained with the aforementioned assumptions. 5.4 The Results In this section, we discuss the numerical results obtained using the ideas presented in this paper. Unless it is explicitly stated, we assume that: (1) all nodes are equipped with enough regenerators that allow all wavelengths to be regenerated, (2) 50% of ®bers are ``new'', and (3) both routes are used in the path-selection of every service-demand. 5.4.1 Impact of Network Transmission Quality on the Regeneration Requirement of Optical Services Fig. 5 shows the impact of the average number of ``new'' ®bers on the regeneration budget of the

network. On the x-axis, we show the three network con®gurations. On the y-axis, we plot the average number of regenerators needed per path. The ®gure shows the requirements for both optical services. As one could guess, we observe that, by far, 10 Gb/s traf®c requires substantially more regenerators. We also notice that, for the simulations performed, a 20% increase in the number of ``new'' ®bers allows for a 36% reduction in the regeneration requirement. It is clear that any cost-effective network design, should always try to have a balance between the cost of these two resources: regenerators and ®ber links. A provisioning software, on the other hand, uses the output of this design in order to minimize the network blocking, as it will be demonstrated below. 5.4.2 Performance Comparison with the Probing Method In this section, we provide comparisons with the algorithm proposed in Section 4.4 and the simple probing-based scheme discussed in Section 4.3. The numerical results demonstrate great enhancements to the blocking performance of the network with an execution time increase of 60% or less. In the following, we provide detailed treatment of the

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M. Ali, D. Penninckx/Provisioning Methods For Bit-Rate-Differentiated Services Table 1. Main assumption for physical impairments. Attribute

LH

ULH

Ampli®er spacing (uniform distribution) in km

From 60 to 110

From 60 to 110

Fiber loss (uniform distribution) in dB/km

New ®bers: From 0.22 to 0.26 Old ®bers: From 0.24 to 0.28

New ®bers: From 0.22 to 0.26 Old ®bers: From 0.24 to 0.28

Slope of ®ber loss taking into account Raman ampli®cation wavelength dependence from 1530 to 1560 nm (in dB/km)

0.01

0.015

p PMD in ps= km

New ®bers: 0.1 Old ®bers: 0.4

New ®bers: 0.1 Old ®bers: 0.4

Transmitter OSNR (dB/0.1 nm)

30

30

Equivalent noise ®gure (dB)

From 7 to 9

Slope of noise ®gure from 1530 to 1560 nm (in dB)

From 0 to 2

1

2

Optical power (dBm)

From 2 to 4

From 0 to 2

Power ¯uctuations at each ampli®er (uniform distribution) in dB

0.4

0.2

Table 2. Typical values of OSNRs (in dB/0.1 nm) for the ®rst (1530 nm) and the 32nd (1560 nm) wavelength for different link lengths, type of ®bers and transmission systems. LH

ULH

Old Fiber

New Fiber

Old Fiber

New Fiber

Fiber Length

1530 nm

1560 nm

1530 nm

1560 nm

1530 nm

1560 nm

1530 nm

1560 nm

200 km 500 km 800 km

23.5 18.8 15.4

25.6 23.4 22.4

24.8 20.5 17.2

26.7 24.8 23.9

26.6 23.3 20.8

28.1 26.6 25.7

27.5 24.7 22.3

28.7 27.5 26.7

Fig. 5. Impact of the percentage of ``new'' ®bers on the regeneration requirement. Load ˆ 0.0.

simulation results. We ®rst provide blocking performance comparisons under different network assumptions, and then discuss the execution time increase.

Blocking Performance. Recall that the probing method attempts at a hop-by-hop solution to the WARR problem. Clearly, if: (1) there are no restrictions on the use of a regenerator at any node (i.e., a free regenerator can be used by any input wavelength to any output wavelength), and (2) there is at least one free regenerator on every node of the route, then the probing-based method has the same performance as that of the optimal. However, in real networks this is clearly not the case. Figs 6 and 7 illustrate the gap between the two approaches with respect to the blocking probability for 2.5 Gb/s and 10 Gb/s traf®c, respectively. In both ®gures, we assume zero load (i.e., we address the impact of signal impairments only). We utilize the network with 50% ``new'' ®bers. Furthermore, the two schemes utilize the same two routes and the blocking

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Fig. 6. Comparison between the blocking performance of probing and the proposed approach. No load, 2.5 Gb/s Traf®c.

comparison is made with respect to the ``Best of Both'' routes. For each scheme, on the x-axis, we provide the percentage of nodes capable of regeneration. This percentage is used as the probability of randomly allocating a regeneration bank at a given node. As expected, when there are either no available regenerators or the number of available regenerators is very high, the two approaches have comparable performance. However, the performance gap between these two extreme points is very large. For example, when the percentage of regenerators is 25% and the traf®c is 2.5 Gb/s, we observe that the blocking probability using the proposed approach is about 80% less than that using the probing method. We also observe that the blocking probability becomes almost ¯at and approaches zero for the proposed approach in the network with 50%, or more, of the nodes being able to regenerate. The probing method reaches the zero blocking when all nodes are equipped with

regeneration. We observe a lower gap in the blocking performance between the two schemes in the case of 10 Gb/s traf®c as shown in Fig. 7. This can be explained by the fact that the regeneration requirement for 10 Gb/s traf®c is higher than that of 2.5 Gb/s traf®c; hence more blocking occurs in the optimal case. Thus, the infeasibility of the path makes the gap smaller than that in the case of 2.5 Gb/s traf®c, where the regeneration requirement is lower. As we increase the load, one can expect that the gap for the two traf®c rates decreases. However, this is mainly true for 2.5 Gb/s and not for 10 Gb/s. Figs 8 and 9 show the results for load ˆ 0.5. The reason behind the almost constant gap in the case of 10 Gb/s for no load and 0.5 load can be attributed to the dual-use of regenerators. The algorithm intelligently uses a regenerator for both wavelength-translation and signal clean-up. To verify this claim, consider for example the 50% regeneration capability con®guration. Table 3 shows the regenera-

Fig. 7. Comparison between the blocking performance of probing and the proposed approach. No load, 10 Gb/s Traf®c.

M. Ali, D. Penninckx/Provisioning Methods For Bit-Rate-Differentiated Services Table 3. All different useful scenarios for 0.5 load and 50% regeneration capability. Load

Impairments

Avg. # of Regenerators Per Path

Blocking Probability

NO YES YES

YES NO YES

1.38 0.647 1.43

0.552 0.023 0.557

tion and blocking performance for all three different scenarios. In Row 1, we show the requirements for impairment-only scenario. Row 2 shows the requirement for wavelength-translation only. The ®nal row shows the requirement for both signal clean-up as well as wavelength-translation. Notice that instead of the sum of the two scenarios individually …1:38 ‡ 0:647 ˆ 2:027†, we have 1.43 average regenerators per path.

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Similar trends are also observed when the network load is varied. Figs 10 and 11 show the blocking performance of the two methods as a function of the network load for the two bit-rates and 50% regeneration capability. We observe that the blocking is ¯at for the 10 Gb/s case for 0.4 load or less. As the load increases, the blocking increases, but with slower rate than that of 2.5 Gb/s case. In the 2.5 Gb/s case, we see an increase of the blocking beyond 0.2 network load and the rate of increase is much higher than that of 10 Gb/s traf®c. Again, this is due to the fact that the signal clean-up requirement for the 2.5 Gb/s service is lower than that of 10 Gb/s service; thus the need for regenerators for wavelength-translation cannot be intelligently shared with existing regenerators already used (at no load) for signal clean-up.

Fig. 8. Comparison between the blocking performance of probing and the proposed approach. Load ˆ 0.5, 2.5 Gb/s traf®c.

Fig. 9. Comparison between the blocking performance of probing and the proposed approach. Load ˆ 0.5, 10 Gb/s traf®c.

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Fig. 10. Comparison between the blocking performance of probing and the proposed approach as a function of network load. 2.5 Gb/s traf®c. 50% regeneration capability.

Fig. 11. Comparison between the blocking performance of probing and the proposed approach as a function of network load. 10 Gb/s traf®c. 50% regeneration capability.

Execution Time. Fig. 12 shows the increase in execution time using the proposed algorithm relative to the probing method. On the x-axis, we vary the network load and on the y-axis, we show the ratio of the average execution time of both schemes. The ®gure shows the results for three different scenarios: no and full regeneration, and 50% regeneration con®guration. All traf®c is 10 Gb/s. We observe that the increase in execution time does not exceed 60% in all cases. The extra time spent provides valuable blocking performance enhancements, however. For example, for the simulations performed, and for 50% regeneration capability and no load, a 21% increase in execution time provides a 16% reduction in blocking probability. Furthermore, the execution time ratio

increases as the number of regenerators increases. This is due to the fact that less blocking occurs in networks with higher node-regeneration probability. Thus, the proposed (optimal) approach consumes more time to ®nd a feasible and an optimized solution. On the other hand, the blocking probability of the probe method remains relatively higher even at higher number of available regenerators in the network; thus consuming less execution time. 5.4.3 Enhancement to the Blocking Performance Through the use of Multiple-Routes It is obvious that increasing the number of routes should provide better chances of enhancing both the

M. Ali, D. Penninckx/Provisioning Methods For Bit-Rate-Differentiated Services

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Fig. 12. Execution time ratio. Time computation of our method divided by the time computation for the probing-based scheme versus load.

Fig. 13. Impact of multiple routes on the blocking performance. 76% regeneration capability and 10 Gb/s traf®c.

blocking performance and the regeneration requirement. However, the set of routes k, should be kept as small as possible to avoid excessive computation time and resource under-utilization.1 Fig. 13 shows the blocking probability for three routing strategies. The ®rst (respectively, the second) strategy assumes that the hop-count (respectively, the impairment) route is the only route used for each connection setup. The third approach, considers solving the WARR problem for both routes and selecting the best for each connection request. On the x-axis, we show two load scenarios: low-load of 0.4 and high-load of 0.8. On the y-axis, we plot the blocking probability. The ®gure is obtained using a 76% percentage of regeneration capability and 10 Gb/s traf®c. From the ®gure, one can observe the

reduction in the blocking probability due to the use of this alternate-routing approach. For example, at 0.4 Load, we observe that the use of multiple routes allowed for a 16% reduction in blocking probability compared with the best performance route (i.e., the Impairment route). Yet, more enhancements (31%) are observed when it is compared with the hop-count. The reductions in the case of 0.8 load are 18% and 22%, for hop-count and impairment routes, respectively. Also, observe that, as expected, the best individual route for low-load is the Impairment route. While the best such route in the case of highload is hop-count. This is due to the fact that, at lowload network state, the dominant need for regeneration is signal clean-up, while at high-load, it is wavelength-translation (the hop-count minimizes the

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Fig. 14. Impact of multiple routes on the regeneration requirement. 76% regeneration capability and 10 Gb/s traf®c.

number of links; thus the need for wavelength translation). Fig. 14 shows the regeneration requirement for the three approaches. The regeneration need is nearly the same, whatever the strategy, because the lightpath length is around the same for both hop-count and impairment. 5.4.4 Bene®ts of Transparency and ServiceDifferentiation We would like to quantify the savings, in terms of OEO devices, due to the use of service differentiation

in the routing. There are three cases. The ®rst one is not to consider impairments in the routing and provide signal regeneration at each hop. This case is referred to as the opaque case. The second approach is to provision according to the traf®c with the highest requirement regardless of the connection requirement. This case is referred to as no service-differentiation. The ®nal case is to assign resources to a service according to its requirements. This later case is referred to as service-differentiation. Fig. 15 shows regeneration requirement under the three different

Fig. 15. The average number of regenerators per path under the three different scenarios: Opaque, no service-differentiation and service differentiation.

M. Ali, D. Penninckx/Provisioning Methods For Bit-Rate-Differentiated Services

assumptions. We utilize the ``50%'' network con®guration and network load of 0.5. All nodes are equipped with regeneration capability. On the x-axis, we show the percentage of 2.5 Gb/s traf®c compared to overall measured traf®c. On the y-axis, we show the average number of regenerators per path. It is evident from the graph the great savings using the servicedifferentiation scheme over both the opaque and noservice-differentiation methods. In particular, for a 60%2:5 Gb=s traf®c mix, the average reduction of number of regenerators is 44% compared to the noservice-differentiation case.

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Comparisons of the above scheme with a probingbased method, revealed substantial enhancements to the blocking performance with a maximum running time increase of 60%. In addition, the use of multiple routes provided reduction in the blocking probability over single-routing schemes. Moreover, the proposed, non-pessimistic, provisioning approach has a major impact on reducing the regeneration budget of the network.

Appendix: Algorithms used in Connection Establishment 6

Summary of Paper

In this paper, we addressed the problem of routing and wavelength assignment of differentiated optical services in hybrid network. Hybrid optical networks are composed of resources, such as ®ber links and photonic/electronic switches, that vary in their capabilities and transmission qualities. These networks are also responsible for the realization of optical services with varying QoS guarantees. In such networks, it is required to have a cost-effective assignment of the optical and electronic resources to these services in order to maximize the revenue of the network operator. This paper dealt with optical services that are de®ned according to their tolerance to transmission impairments. We divided the problem into two phases: routing and wavelength assignment and regeneration reservation phases. In the routing phase, a set of k-routes are generated to select from in the second phase, where each route optimizes a speci®c aspect of the problem (e.g., number of hops, maximum accumulated noise, etc.). The second phase, using the information about the resources along each route, attempts at ®nding the best wavelength allocation on each route such that signal quality meets the service-level agreement (SLA). The second phase also uses the minimum number of regenerator ports on intermediate nodes for the purpose of wavelength translation and signal cleanup.

Fig. 16. A function that ®nds the longest transparent segment from a given regenerated point to the egress node.

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M. Ali, D. Penninckx/Provisioning Methods For Bit-Rate-Differentiated Services

Fig. 17. A function used by function ScanSegment to ®nd the best wavelength that maximizes the length of the transparent segment.

Notes 1. Although, in this paper, we do not address the protocol and signaling issues, one can imagine that it is bene®cial to lock resources along the routes before solving the WARR problem. As the number of routes used per connection increases, more resources are temporally locked which leads to resource underutilization. In addition, contention between different dynamic connection setups, for the same resource, increases.

References [1] N. Golmie, T. Ndousse, D. H. Su, A differentiated optical services model for WDM networks, IEEE Communications Magazine, vol. 38, no. 2, (February 2000), pp. 68±73. [2] M. Ali, G. Chiruvolu, D. Elie-Dit-Cosaque, L. Tancevski, QoS-based routing in optical networks, in: Optical Fiber Communications (OFC), vol. 1, (March 2002), pp. 100±102. [3] M. Ali, D. Elie-Dit-Cosaque, L. Tancevski, Network optimization with transmission-based routing, in: The 27th European Conference on Optical Communication (ECOC), vol. 1, (Amsterdam, The Netherlands, September 2001), pp. 42±43. [4] A. Chiu et al., Impairments and other constraints on optical layer routing, internet draft, work in progress, draft-ietf-ipoimpairments-02.txt, (February 2002). [5] M. Ali, Transmission-Ef®cient Design and Management of Wavelength-Routed Optical Networks, (Kluwer Academic Publishers, 2001). [6] J. Strand, A. Chiu, R. Tkach, Issues for routing in the optical layer, IEEE Communications Magazine, vol. 39, no. 2, (February 2001), pp. 81±87. [7] R. Ramaswami, K. N. Sivaraja, Optical Networks: A Practical Perspective, second ed. (San Francisco, CA, Morgan Kaufmann Publishers, 2001). [8] D. Penninckx, O. Audouin, Optically preampli®ed systems: de®ning a new eye aperture, in: OFC'98, (San Jose, CA, USA,

February 1998). Poster Presentation, WM36. [9] E. Ciaramella, Introducing wavelength granularity to reduce the complexity of optical cross connects, IEEE Photonic Technology Letters, vol. 12, no. 6, (June 2000), pp. 699±701. [10] L. Noirie, C. Blaizot, E. Dotaro, Multi-granularity optical cross-connect, in: European Conference on Optical Communication, ECOC'00, 9.2.4, (Munich, Germany, September 2000), pp. 264±265. [11] R. Ganguly, E. Modiano, Distributed algorithms and architectures for optical ¯ow switching in WDM networks, in: IEEE Symposium on Computers and Communications, ISCC'00, (Antibes, France, July 2000), pp. 134±139. [12] X. Yuan, R. Melhem, R. Gupta, Distributed path reservation algorithms for multiplexed all-optical interconnection networks, IEEE Transactions on Computers, vol. 48, no. 12, (December 1999), pp. 1355±1363. [13] A. Shami, et al., Multi-path based distributed routing algorithm for WDM routed networks, in: The 27th European Conference on Optical Communication (ECOC), vol. 1, (Amsterdam, The Netherlands, September 2001), pp. 44±45. [14] L. Kejie, X. Gaoxi, I. Chlamtac, Blocking analysis of dynamic lightpath establishment in wavelength-routed networks, in: IEEE International Conference on Communications (ICC'02), vol. 5, (New York, NY, USA, April/May 2002), pp. 2912±2916. [15] A. Shami, C. Assi, I. Habib, M. A. Ali, Performance evaluation of two GMPLS-based distributed control and management protocols for dynamic lightpath provisioning in future IP networks, in: IEEE International Conference on Communications (ICC'02), vol. 4, (New York, NY, USA, April/May 2002), pp. 2289±2293.

Maher Ali is currently a research scientist at Alcatel Research and Innovation Center in Plano, TX. Dr. Ali received a B.S. in Computer Science from Yarmouk University, Jordan in 1993 and a Ph.D. degree in Computer Science from the University of NebraskaLincoln in 2000. His research interests are in the general area of computer networking. Dr. Ali is a member of the IEEE. Denis Penninckx was born in Paris in 1970. He graduated from the Ecole Normale SupeÂrieure de Lyon (France) and from the EÂcole SupeÂrieure d'EÂlectricite (Gif/Yvette, France) in 1993. He received his Ph.D. degree on optical modulation formats from the EÂcole Nationale SupeÂri-eure des TeÂleÂcommunications (Paris) in 1997. He joined Alcatel Research Centre in 1994 to work ®rst on modulation formats and polarization-mode dispersion. He then joined the research team on optical networking, working ®rst on packet switching and now on transparent backbone networks. Dr. Penninckx, associate member of the Alcatel Technical Academy, has been in the technical committee of CLEO US from 2001 to 2003. He has authored or co-authored more than 70 technical papers and 30 patents on all afore-mentioned topics.