Multi-Granular Optical Cross-Connect: Design, Analysis

Zervas et al. VOL. 1, NO. 1 /JUNE 2009/J. OPT. COMMUN. NETW. 69

Multi-Granular Optical Cross-Connect:Design, Analysis, and Demonstration

Georgios S. Zervas, Marc De Leenheer, Lida Sadeghioon, Dimitris Klonidis, Yixuan Qin,Reza Nejabati, Dimitra Simeonidou, Chris Develder, Bart Dhoedt, and Piet Demeester

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Abstract—A fundamental issue in all-optical switch-ing is to offer efficient and cost-effective transportservices for a wide range of bandwidth granularities.This paper presents multi-granular optical cross-connect (MG-OXC) architectures that combine slow(ms regime) and fast (ns regime) switch elements, inorder to support optical circuit switching (OCS), op-tical burst switching (OBS), and even optical packetswitching (OPS). The MG-OXC architectures are de-signed to provide a cost-effective approach, while of-fering the flexibility and reconfigurability to dealwith dynamic requirements of different applications.All proposed MG-OXC designs are analyzed and com-pared in terms of dimensionality, flexibilityÕreconfigurability, and scalability. Furthermore, nodelevel simulations are conducted to evaluate the per-formance of MG-OXCs under different traffic regimes.Finally, the feasibility of the proposed architecturesis demonstrated on an application-aware, multi-bit-rate (10 and 40 Gbps), end-to-end OBS testbed.

Index Terms—Multi-granular optical cross-connect;Optical circuit switching; Optical burst switching;Simulation analysis; Demonstration.

I. INTRODUCTION

A generation of distributed network-based applica-tions that combine scientific instruments, distrib-

uted data archives, sensors, computing resources, andmany others are emerging. Each application has itsown traffic profile, resource usage pattern, and differ-ent requirements originating in the computing, stor-

Manuscript received January 9, 2009; accepted January 12, 2009;published June 1, 2009 �Doc. ID 110468�.

G. S. Zervas, L. Sadeghioon, R. Nejabati, Y. Qin, and D.Simeonidou are with the Photonic Networks Research Lab, Schoolof Computer Science and Electronic Engineering, University ofEssex, Wivenhoe Park, CO4 3SQ Colchester, UK (e-mail:[email protected]).

M. De Leenheer, C. Develder, B. Dhoedt, and P. Demeester are withthe Department of Information Technology, Ghent University-IBBT,Gaston Crommenlaan 8 bus 201, 9050 Gent, Belgium (e-mail:[email protected]).

D. Klonidis is with the Athens Information Technology Centre,Athens, Greece.

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ge, and network domains [1]. Dedicated networks doot offer sufficient flexibility to satisfy the require-ents of each application type, nor are they economi-

ally acceptable. Hence it is vital to understand andedefine the role of networking, to support applica-ions with different requirements, and also offer ser-ice providers a flexible, scalable, and cost-effectiveolution. A dynamic optical network infrastructureith the ability to provide bandwidth granularity atifferent levels is a potential candidate. In this way,he network can adapt to application requirementsnd also support different levels of quality of serviceQoS). However, care must be taken to devise a solu-ion that remains scalable and cost-effective (see alsoection II.C).A multi-granular optical switched network is able to

upport dynamic wavelength and sub-wavelengthandwidth granularities with different QoS levels. Asuch, the network will support the three basic switch-ng technologies in WDM networks: optical circuitwitching (OCS), optical packet switching (OPS), andptical burst switching (OBS).In OCS networks, bandwidth granularity is at theavelength level since one or more wavelengths arellocated to a connection, while connectivity betweenhe source and destination is established using a two-ay reservation, which is in general a time-

onsuming procedure. The OCS scheme is suitable forpplications that need continuous bandwidth for aelatively long duration of time. However, this schemes neither sufficiently flexible nor bandwidth efficiento support applications that require sub-wavelengthandwidth granularity in an on-demand fashion or forshort duration of time.OPS technology makes it possible to achieve sub-avelength bandwidth granularity and exploit statis-

ical multiplexing of bursty traffic flows. In OPS net-orks, one or more IP packets with similar attributesre aggregated in an optical packet and tagged withn optical header. This scheme does not need advanceeservation, and it can provide on-demand connectiv-ty by imitating best-effort IP packet routing in the op-ical domain. These features make OPS technology auitable candidate for applications that need trans-

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70 J. OPT. COMMUN. NETW./VOL. 1, NO. 1 /JUNE 2009 Zervas et al.

mission of small data sets in an on-demand manner[2]. However, the lack of practical optical buffering so-lutions, together with the high cost of switch fabricsthat meet the constraints imposed by OPS, make thistechnology difficult to implement and deploy in prac-tice.

OBS combines the advantages of OCS and OPS [3].The fundamental premise is the separation of the con-trol and data planes, and the segregation of function-ality within the appropriate domain (electronic or op-tical). Prior to data transmission, a burst controlheader (BCH) is created and sent towards the desti-nation. The BCH is typically sent out-of-band over aseparate signaling wavelength and processed elec-tronically at intermediate OBS routers. It informseach node of the impending arrival of the data burst,and in turn drives the allocation of an optical path.Data bursts remain in the optical plane end-to-endand are typically not buffered as they transit the net-work core. The main advantages of OBS are that, un-like OCS networks, the optical bandwidth is reservedonly for the duration of the actual data transfer, andthus OBS increases bandwidth efficiency. Likewise, incontrast to OPS networks, OBS is not based on best-effort routing and potentially can be implementedwithout buffers.

In order to migrate from a strictly wavelengthgranular network (OCS) to a sub-wavelength one(OBS or even OPS) and/or also consider the possibilityof hybrid OCS/OBS type of networks (Fig. 1), switch-ing technologies with speeds on a millisecond range

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own to the nanosecond range must be considered.he network resource reservation can be realized byrst sending a reservation message (e.g., RSVP Pathessage for GMPLS or LOBS [4], BCH for OBS) to

he network. The control mechanism then recognizeshether the data unit requires slow switching (usu-lly long burst or circuit) or fast switching (usuallyhort burst or packet). In the first case, the slowwitch element is dynamically reconfigured so thathen the long data set arrives, it is routed to the ap-ropriate output port. In the other case, the short datanit (burst or packet) is routed through the fastwitch, either by directly connecting incoming wave-engths or using pre-established soft-permanent con-ections through the slow switch to allow reconfig-rability (see Section III for more details).OCS can utilize millisecond switching technologies

fficiently, whereas this switching speed causes band-idth inefficiency and unpredictability for the perfor-ance of OBS, especially under high network load.his is mainly caused by the high overhead incurredy large offset times required to configure slowwitches. Indeed, the throughput of a switch is defineds /Toffset+Tdata, where Tdata is the length of the actualata in time, and Toffset is the offset time between theontrol message and the data. MEMS switches (micro-lectro-mechanical systems) typically have a switch-ng time of around 10 ms, and thus provide a through-ut of more than 95% on a 10 Gbps system with datauration of 200 ms. If only 1/10th of this data is sentwhich still amounts to 25 MBytes of data), then the

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switch’s throughput decreases to 67%. This effect be-comes even more severe when the bandwidth is in-creased, for instance, to 40 or even 160 Gbps, or whenOPS (data durations on the nanosecond scale) must besupported. An SOA-based switch (semiconductor opti-cal amplifier) can achieve nanosecond switchingspeeds and is thus much better adapted to support thefull range of data sizes required for OCS, OBS, andOPS.

The ideal solution would thus consist of deployingfast switches of large dimension and low cost; how-ever, these do not exist at this time (a brief review ofexisting switching technologies is provided in SectionII.A). Therefore, one possible solution is an opticalcross-connect (OXC) architecture that combines bothslow (e.g., MEMS) and fast (e.g., SOA-based) switch-ing elements. This way, users and applications can de-cide on slow or fast network provisioning, and addi-tionally the network service provider can optimizebandwidth utilization by allocating wavelengths orlightpaths according to the traffic’s switching needs.Furthermore, our previous work [22] has shown thecost-effectiveness of the proposed approach on the net-work level.

In conclusion, the multigranular OXC (MG-OXC)has a number of distinct advantages over traditionalsingle-fabric switches:

• Bandwidth provisioning and switching capabilityat fiber, wavelength, and sub-wavelength granu-larities;

• Agility and scalability of switching granularitiesproviding a dynamic solution;

• Fast reconfigurability and flexibility on the elec-tronic control of switching technologies;

• Cost-performance efficiency by offering an opti-mal balance between slow and fast switch fabrictechnologies.

The remainder of this paper is organized as follows.We first review existing switch fabric technologies forpossible deployment (Section II.A) and then discussalternative proposals for multi-granular opticalswitching in Section II.B. Section III proposes differ-ent MG-OXC architectures and presents an analysison the dimensionality, scalability, and flexibility of thedesigns. Simulations are used to evaluate the MG-OXC for various traffic and design parameters in Sec-tion IV. Furthermore, in Section V, we demonstrate anMG-OXC based on MEMS for circuits or long burstsand SOA-MZI for medium to short bursts or opticalpackets. Results are shown for an end-to-end,application-aware, multi-bit-rate and QoS-enabled(based on bandwidth and latency parameters) OBSnetwork testbed. Finally, Section VI summarizes ourconclusions.

II. RELATED WORK

. Optical Switching Technologies

This section briefly reviews the most prominentwitching technologies available and comments onheir usability in different network environmentsOCS, OBS, OPS).

Three main categories considered for optical switchabric selection [5] are a) signal quality, b) configura-ion, and c) physical performance. Each category has aumber of attributes [6], which are listed below:• Signal quality is largely determined by the bit er-

ror rate (BER) and the cascadability of the switchfabric. Important parameters are signal-to-noiseratio, jitter, amplitude distortion, crosstalk, andextinction ratio.

• Configuration is mostly related to the implemen-tation of the switch and is determined by its scal-ability, blocking characteristics, and cost-effectiveness. Further design considerationsinclude control requirements, dynamic range, po-larization dependence, degree of multicast,latching/non-latching, promptness (store-and-forward versus cut-through), upgradeability,power requirements, and size.

• Finally, the physical performance of a switch isdetermined by optical bandwidth, switchingspeed, insertion loss, bit rate limit, bit pattern de-pendence, uniformity, and optical transparency.

In [7], Baldine et al. realized an OBS testbed usingEMS OXCs from ATDnet. In [8,9], NTT and Fujitsu

emonstrated burst switching with GMPLS-basedwo-way signaling protocol, utilizing planar lightwaveircuit (PLC) and MEMS switches. In [10], commer-ial PLC switches were adopted to construct a 1616on-blocking switch matrix with a switching speed of

ess than 3 ms. OBS schemes with hybrid optical andlectrical switching technologies have been investi-ated in the past [11]. A recent study demonstratedhat a PLZT switch (lead lanthanum zirconate titan-te, [12]) with shared wavelength conversion allowedariable-length 3.5 ns OBS. A photonic random accessemory (RAM) was used in [13] to write and read

igh-speed asynchronous burst optical packets. Inhis paper, the main criteria used in the decision pro-ess are the switching time and scalability. Thus, ac-ording to Yoo et al. in [5], Table I identifies possiblewitch fabrics for the development of a multi-granularwitch. A detailed discussion based on the attributesentioned above can be found in Wei et al. [11] andapadimitriou et al. [6]. Clearly, one of the most ap-ropriate slow switching technologies is the opticalEMS switch, since it is already a mature technology

nder production and because of the high dimensionsvailable at low cost [14,15]. On the other hand, mostast switch matrices (ns regime) listed in Table I are

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still in the research stage; some are not yet integratedinto a single device (e.g., wavelength routing switch)or are highly sensitive to polarization (e.g., SOA-basedswitches). As such, it is not yet possible to select themost appropriate technology at this stage.

B. Multi-Granular Optical Cross Connects

The principle of multi-granular optical cross-connects that can switch traffic at fiber, waveband,and wavelength granularities [16–18] has been pro-posed to reduce the cost and complexity of traditionalOXCs. The MG-OXC is a key element for routing highspeed WDM data traffic in a multi-granular opticalnetwork. A three-layer switching fabric consisting of afiber cross-connect (FXC), a band cross-connect (BXC),and a wavelength cross-connect (WXC) was presentedin [19,20], and the application of such three-layer MG-OXC architectures to metro-area networks was dem-onstrated in [21]. The work presented in this papercan be considered as complementary to the studiesmentioned above. Instead of extending the granular-ity towards higher capacities (e.g., wavebands to fullfibers), we propose OXC architectures that are able toswitch at the sub-wavelength level. By combining thetwo extensions, the full range of bandwidth granulari-ties can be supported by a single OXC design.

C. Cost Effectiveness

In our previous work [22], we have shown thatmulti-granular switching also provides economic ad-vantages on the network level, which provides furthermotivation for the cost-effectiveness of the proposedapproach. For this, an ILP-based network dimension-ing algorithm was introduced to compare multi-granular switching with approaches based on a singletechnology (MEMS for slow switching, SOA for fast).Results indicated that significant cost savings can beobtained when implementing multi-granular opticalswitching. Another important conclusion was that thereconfigurable MG-OXC design (see Section III.A)leads to only a negligable cost increase compared tothe non-reconfigurable design. Furthermore, reduced

TABSWITCH FABRICS FOR OCS, OBS, AND OPS

Switching time

Opto-mechanical switch 4 msOptical MEMS 3D: �10 ms, 2D: �3 mThermo-optical PLC �3 msPLZT switch �20 nsSemiconductor optical phase array �30 nsWavelength routing switch �1 nsSOA broadcast-and-select �1 nsSOA cross-point �1 nsOptical RAM �1 ns

ode costs can be achieved as well, in order to mini-ize scalability problems corresponding to emerging

ast switching fabrics.

III. MULTI-GRANULAR OPTICAL CROSS CONNECTARCHITECTURES

This section presents, analyzes and evaluates differ-nt architectures aiming to support OCS, OBS, andPS (or even a combination of them, e.g., hybrid OCS/BS) with a single design.

. MG-OXC Design

Before discussing the proposed switch designs, wetate our design goals. We first note that neitheravelength conversion nor buffering capabilities arevailable, as these technologies are both costly andmpractical.

• Each design must support multi-granular opticalswitching and consist of both slow and fastswitching fabrics.

• The architectures must be non-blocking in thesense that any input wavelength can be con-nected to any output fiber. The stricter formwhere any input wavelength can be connected toany output wavelength is not achievable since weassume no wavelength conversion is available.

• A number of wavelengths of each fiber should beable to access the fast switch, although only lim-ited fiber-wavelength pairs can do so simulta-neously.

• We favor designs that allow the set of fiber-wavelength pairs, which have access to the fastswitch, to be reconfigurable. However, we alsoshow switch designs in which this functionalitycan only be achieved through manual interven-tion. In the following paragraph, we explain re-configurability in more detail.

• The design should be able to scale in fast or slowswitch ports depending on network requirements(i.e., adding new wavelengths and/or links)

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• Lastly, the number of fast switch elements shouldbe limited as much as possible, in order to createa cost-effective design.

An additional design constraint is that neitherwavelength conversion nor buffering capabilities areavailable. It is particularly important to provide aflexible and scalable solution both in switching dimen-sionality and in bit rate. The architecture is deter-mined by two fundamental design choices and consid-ers the configuration and connectivity of the slow andfast switch fabrics separately. The first choice is re-lated to the slow switch and is based on the well-defined concept of wavelength or link modularity. Theformer means that identical wavelengths from differ-ent fibers are switched in the same fabric, whereaslink modularity implies that all wavelengths of a linkare grouped in a switching block. The second part ofthe design introduces the fast switch elements to themulti-granular architecture and is based on the rela-tive connectivity to the slow switch fabric. Possible ap-proaches are either parallel or sequential integration,and this choice has important consequences on theconfigurability and dimensions of the designs. InTable II, a number of notations are introduced thatare relevant for the design and analysis of the MG-OXC. Each architecture consists of F input and F out-put fibers, labeled f1 to fF. The input fibers are first

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TABLE IINOTATIONS FOR ANALYSIS OF DIMENSIONS AND SCALABILITY

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plit into different wavelengths by a demultiplexerDEMUX, by using for example an AWG (arrayedaveguide grating)). Before leaving the OXC, wave-

engths are multiplexed (MUX, e.g., AWG) on a fiber.irst, the conceptually simple parallel designs (Figs. 2nd 3) provide no connectivity between the slow andast switch elements, which implies that there is noexibility to rearrange slow and fast wavelengths, un-

ess it is done manually. In the link modular design,he role of the multiplexing devices (e.g., optical cou-lers) that are attached to the output of the slowwitches, is to ensure the non-blocking behavior asreviously defined. The following designs (Figs. 4 and) are referred to as the sequential architectures;hese provide two-stage switch connectivity for provi-ioning of fast cross-connections. The fast optical portsan be reached through the slow switches and as suchllow (re)configuration of fast connections, sharedmong all slow switches in order to combine wave-engths from all incoming fibers. Figure 4 is based onhe assumption that not only the slow, but also theast switch is configured in a wavelength modularashion. However, it is also possible to share a fastwitch block between different wavelengths, in ordero reduce the number and dimensions of the fastwitch fabrics. Also note that for the sequential wave-ength modular design, the parameter K is given by=�w=1

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.e., K represents the number of distinct wavelengthstotal W) that are switched fast on at least 1 fiber. Theequential link modular design also requires the cou-1By definition, the Kronecker delta � equals 1 if i= j, 0 otherwise.

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pling devices at the output of the slow switch, in orderto adhere to the non-blocking requirement. In Fig. 5,the assumption with regard to the wavelength modu-larity of the fast switch has been made as well. Again,further reductions in fast switch ports and fabrics arepossible by sharing a fast block between differentwavelengths.

B. Dimensions and Scalability

To analyze the dimensions in terms of the numberof cross-connects required and the number of ports oneach cross-connect, refer to the notations as listed inTable II. The assumption has been made that all fi-bers support an identical number of fast wavelengthsY:

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Fig. 5. (Color online) Sequential link modular architecture.

he different architectures, while also indicating theirimensions.

. Qualitative Analysis

In this subsection, we discuss qualitative advan-ages and disadvantages between the proposed archi-ectures. The focus lies on demonstrating additionaleatures or shortcomings related to the flexibility, re-onfigurability, and construction of these switch de-igns. Since a major design goal of the MG-OXC is costfficiency, the focus should be on minimizing both theumber of fast switching fabrics and ports. Table IIIoes not allow general conclusions to be drawn, as aomparison between the sequential and parallel ap-roaches requires us to make assumptions on theumber of fibers F, the number of fast wavelengths Y,nd the number of distinct fast wavelengths K. Recall,owever, that the sequential designs offer reconfig-rability of fast wavelengths, which the parallel archi-ectures lack (see Section III). In Fig. 4, the sequentialesign assumes identical wavelengths are switched insingle fast block. A further reduction of fast blocks

nd/or ports is possible by allowing different wave-engths to share a single fast block, as depicted in Fig.. In that case, however, the switch’s control unit mustrevent identical wavelengths from arriving at theUX of a single fiber. Another possibility is to intro-

uce wavelength conversion inside the MG-OXC, a so-ution that is currently impractical due to its high costnd technological immaturity.As previously stated, an important distinction lies

n the modularity of the switch designs, which has aajor influence on scalability. The link modular ap-

roaches easily allow a new link to be added to an ex-sting switch, although extending a link with an extraavelength is much less straightforward. Likewise,

he extensibility of the wavelength modular ap-roaches is straightforward when adding a wave-ength, but it is much less convenient to introduce aew link in the switch.

TABLE IIICOUNT AND DIMENSIONS OF SLOW AND FAST SWITCHES

Type Modularity Count Dimensions

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Depending on integration and/or production costs, apotential advantage can arise for architectures havingfast switches, whose input dimensions are smallerthan the number of output ports. This is obviously thecase for the parallel link modular and sequentialwavelength modular approaches.

Finally, the limited scalability of fast switchingtechnologies (e.g., SOA up to 32�32 ports) may provean issue when larger fast switch blocks are required.It is, however, possible to combine multiple switchblocks in a multi-stage design as shown in, e.g.,[23,24], but careful analysis of physical performance(signal loss, BER, etc.) is advised.

IV. SIMULATION ANALYSIS

In this section, simulation analysis is used to pro-vide insight in the behavior of the MG-OXC [25]. Theimplementation allows us to evaluate an MG-OXC ina generic way, independent of architectural details(modularity, reconfigurability). Note that for fixed F,W, and Y values, the designs presented in the previ-ous section are functionally equivalent. A comparisonbetween MG-OXC and traditional, single-speed OXCs(slow only, fast only) is presented, and results aregiven for varying traffic load, fractions of slow/fasttraffic and number of slow/fast ports available. How-ever, we start with introducing the different ap-proaches to wavelength assignment, which are neces-sary for mapping incoming data bursts to a suitablewavelength. For a general overview of the node simu-lations, and to observe the different steps in whichtraffic is processed, refer to Fig. 6.

A. Wavelength Assignment

The introduction of an MG-OXC in a network effec-tively creates a wavelength partitioning, by groupingwavelengths that are switched on the same type ofswitching fabrics. As such, an algorithm is required toassign generated traffic to a suitable wavelength par-tition and the available wavelengths within a parti-tion. This algorithm will be executed at the network’sedge, thus before entering the all-optical data trans-

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ort network (see Fig. 6). In the following, the as-umption was made that only two partitions (corre-ponding to slow and fast) are introduced.As shown in Fig. 7, generated traffic is first classi-

ed in slow (arrival rate �s) and fast ��f� traffic flows,y inspecting the offset time Toffset between the bursteader and the actual data burst. Obviously, for slowraffic it holds that Toffset�Tslow (Tslow is the switchingpeed of the slow switch), while Toffset�Tslow is true forast traffic (Tfast is the switching speed of the fastwitch fabric). Based on this classification, a numberf alternatives are now possible for assignment of traf-c to the wavelength partitions.The approaches differ in the way traffic is trans-

erred between the slow and fast wavelength parti-ions. Simple wavelength assignment is the most ba-ic approach, whereby slow bursts are assigned to thelow wavelength partition, and the burst is dropped inase no free wavelength is available. Fast bursts areonsidered for assignment to the fast wavelength par-ition in a similar way. The slow-to-fast approach dif-ers from the simple algorithm by allowing slowursts on the fast wavelengths, only in case theseannot be accommodated on the slow wavelengths.he corresponding fast-to-slow wavelength assign-ent allows transfer of fast bursts onto slow wave-

engths (again only in case the fast burst cannot be as-igned to a fast wavelength). We motivate the use ofhis algorithm as follows: although the slow switchannot be configured in time for a fast burst, it is pos-ible that the preceding (slow) burst requests theame output, and thus reconfiguration of the switch isot required. Finally, the greedy approach allowsransfer of traffic between both wavelength partitions,gain only when no available capacity can be found forhe original wavelength assignment.

Let �sf be the transfer rate from the slow to the fastavelength assignment block, and �fs from fast to

low. Then Table IV shows the transfer rates for theifferent wavelength assignment approaches. Here, Psnd Pf represent the blocking probabilities of the slownd fast wavelength assignment blocks and are giveny (assuming Poisson arrivals)

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Note that in case of greedy wavelength assignment,Ps and Pf depend on each other, and thus an iterativesubstitution is required to obtain the respective block-ing probabilities.

To demonstrate the influence of these alternatives,Fig. 8 shows the load remaining after wavelength as-signment, i.e., the plot shows the total load at point bfor varying generated loads at point a (Fig. 6). This re-sult was obtained by assuming Wf=2 and �=�f /�s+�f=0.2, which reflects the expected low number of(expensive) fast wavelengths. It also follows that �represents the fraction of generated fast traffic to thetotal generated (slow and fast) traffic. Even thoughthe total load after wavelength assignment is similarfor the various approaches, Fig. 9 provides more in-sight into which type of traffic is favored. The figureshows the fraction of fast traffic to the total traffic af-ter wavelength assignment, and this for a varying to-tal generated load. In other words, we plot the fractionof fast traffic to the total traffic at point b in Fig. 6 anddo this for various load averages at point a. Clearly,the fast-to-slow approach allows more fast traffic than

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TABLE IVTRANSFER RATES (NUMBER OF BURSTS PER TIME UNIT)BETWEEN SLOW AND FAST WAVELENGTH ASSIGNMENT BLOCKS

Simple Slow-to-fast Fast-to-slow Greedy

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he greedy approach, since the latter also allows slowursts to use valuable fast wavelengths. It should beoted, however, that, although not shown, the behav-

or of fast-to-slow converges to greedy for increasingalues of �. Both the simple and slow-to-fast algo-ithms preserve only small fractions of fast traffic andre thus not well-adapted to support a multi-granularptical network scenario, as a non-negligable amountf fast traffic will be lost because of inappropriateavelength scheduling. Since our main interest is theffect of fast traffic and fast wavelengths, the simula-ion results presented in Subsection IV.B have beenade using the fast-to-slow wavelength assignment

lgorithm. As mentioned before, another importantecision is how bursts are assigned to individualavelengths within a partition. Strategies such asrst-fit or best-fit have previously been investigated

n, e.g., [26,27]; however, this subject falls outside thecope of this work. The simulation studies in Subsec-ion IV.B assume a first fit strategy.

. Single Node Simulations

This section presents discrete event simulation re-ults of several OXC alternatives (slow only, fast only,nd MG-OXC). All designs support 2 input and 2 out-ut fibers, each fiber carrying 10 wavelengths. Nei-her wavelength conversion nor buffering capability isresent in any of the switch designs. Each incoming

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data burst has a 50% probability of choosing the firstoutput fiber. The bandwidth of each wavelength is10 Gbps, and traffic is generated according to a Pois-son process with an average inter-arrival time of15 ms. Data sizes follow an exponential distribution,with a varying average to establish the generatedload. Because of the limited scale of currently de-ployed OBS networks,2 there is no conclusive dataavailable on a number of relevant traffic parameters.Thus, to control and evaluate the influence of differenttraffic types, the offset times between the controlpacket and data are modeled as a 2-phase hyper-exponential distribution. The probability density func-tion (pdf) f is given by f=�� fslow+�� ffast, with �+�=1 and � and � representing the fractions of gener-ated slow and fast traffic.3 The pdf of the slow fslow (re-spectively fast ffast) traffic is an exponential distribu-tion with average 100 ms (respectively 10 ns). Theslow switching fabric has a switching speed of Tslow=10 ms, while the fast switch has Tfast=1 ns. Thesevalues are representative for a MEMS-based (respec-tively SOA-based) switch [5,6]. This leads to 1−e−0.1

=9.5% of slow traffic that actually belongs to fast traf-fic, and an identical fraction of generated fast trafficwill have Toffset�Tfast.

In the following subsections, we show the perfor-mance of the MG-OXC switch and compare the resultsto designs composed of a single switch fabric (slowonly, fast only). To allow fair comparison of the results,the wavelength assignment algorithm is also appliedin case single-fabric designs are used. This way, theoffered traffic pattern at the switches’ input ports isidentical in all cases. As such, wavelengths are alsopartitioned in these single-fabric scenarios, eventhough the switching speeds are identical for all wave-lengths. The fast-to-slow wavelength assignment algo-rithm (Subsection IV.A) was implemented, togetherwith a first-fit approach for mapping data bursts on aspecific wavelength within a partition. The resultsshown focus on the total loss rate of the switch; burstscan be lost either due to contention or because theswitching speed is insufficient for a given burst.

1) Varying fraction of fast traffic: In the first experi-ment, 2 wavelengths are available in the fast parti-tion, while the remaining 8 are allocated for the slowpartition. Simulations were performed to evaluate theinfluence of the fraction of fast traffic for the threeswitch designs. The resulting Fig. 10 shows the totalloss rate (i.e., ratio of dropped traffic to the offered

2OBS is still considered an immature technology, and as such OBStestbeds/prototypes are composed of at most a few nodes.

3Note that this arrival model does not generate these precise frac-tions of slow and fast traffic. For bursts generated according to fslow,it is still possible that Toffset�Tslow. Using the cumulative distribu-tion function of an exponentially distributed variable, this holds forthe following fraction of traffic: P�ToffsetTslow�=1−e−Tslow/Toffset. Thesame argument holds for fast traffic, where T �T .
offset fast
oad measured at point c in Fig. 6) for a varying of-ered load (point b in Fig. 6). First observe that, forow loads, the relatively high loss rates can be attrib-ted to the fraction of fast traffic that has an offsetime lower than the fast switching speed. However,ome of these bursts can still be switched correctly asonsutive bursts taking the same output port does notequire reconfiguration of the switch fabric (this ex-lains the loss rate close to 6.5% of the fast only de-ign in comparison to the predicted 9.5%).Then, an increasing fraction � of fast traffic causes

igher loss rates, since the number of fast switchingorts remains fixed (0 for the slow only, 2 for the MG-XC). This does not apply to the fast only design (only

hown for �=0.2), whose performance is very similaror all fractions of fast traffic. Also, it is readily appar-nt that the MG-OXC outperforms the slow only de-ign for all values of �. Another observation is that theG-OXC offers loss rates similar to the fast only de-

ign, unless high fractions of fast traffic are generated�=0.5 and 0.8). This is not surprising considering themall number of fast switching ports available to theG-OXC.2) Varying number of fast wavelengths: In the fol-

owing experiment, the generated traffic consisted of0% fast traffic ��=0.8�. Now, simulations focus onarying the number of slow/fast wavelengths in eachartition and hence also the exact number of slow/fastavelengths available to the MG-OXC. Figure 11

hows the total loss rate (point c in Fig. 6) for a vary-ng offered load (point b in the same figure), where onean immediately observe that an increased number ofast wavelengths results in a lower loss rate. That thisesult holds even for the slow only designs is due tohe use of the fast-to-slow wavelength assignment andhe simulation setup: the initial switch configurationonnects the top input and output fibers (and likewiseor the bottom fibers), and traffic is generated with a

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50% probability of choosing either output fiber. Conse-quently, more or less half of the traffic on the Wf wave-lengths can be switched correctly, and this explainswhy increasing values of Wf reduce the total loss rate.As before, the MG-OXC can provide an overall im-proved loss performance compared to the slow only de-sign (behavior of slow only and MG-OXC are similaronly for high loads and a severely under-dimensionedfast switching block). For high numbers of fast wave-lengths �Wf=8�, the loss rate of the MG-OXC ap-proaches the performance of the fast only design. Noteagain that results of the fast only design are shownonly for Wf=8, as other values for Ws lead to very simi-lar loss rates. A final observation is that, although notshown, the loss rate of the slow only design is slightlyhigher in case greedy wavelength assignment is used,due to an assignment of fast bursts to slow wave-lengths.

In conclusion, this section clearly demonstratedthat an MG-OXC, equipped with only a limitedamount of fast ports, can offer significant improve-ments in loss rates when compared to a slow only de-sign. Furthermore, as long as the mismatch betweenfast traffic and fast wavelengths remains within ac-ceptable bounds, the MG-OXC can approach the per-formance levels offered by a fast only design.

V. DEMONSTRATION OF MG-OXC ARCHITECTURES IN AHYBRID NETWORK TESTBED

The functionality and performance of the multi-granular switching concept has been evaluated andexperimentally demonstrated on an application-awaremulti-bit-rate OBS testbed at University of Essex[28]. The application-aware core OBS router utilizes aPowerPC processor embedded in an FPGA and a MG-OXC composed of a fast and widely tunable SG-DBR(sample grating distributed Bragg reflector) laser, a

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D MEMS switch, and a fast SOA-MZI switch. Theulti-granular switch fabric is wavelength selective

nd is controlled by extraction and processing of thencoming BCH through a clock and data recoveryCDR) and a word alignment unit (WAU). Then theeader processing block (HP) is used to retrieve all theequired information from the BCH and the headere-insertion (HRI) unit is used to re-insert the BCH onhe control plane lambda. The BCH consists of severalelds as illustrated in Table V. The class of serviceeld (CoS) explicitly determines the latency require-ents of the burst and thus selects the appropriate

witch fabric. The offset time together with the burstength, wavelength (Burst �), source (Src) and desti-ation (Dest) provide detailed configuration param-ters for either the slow or fast switch fabric. ThePGA provides the appropriate electronic control sig-als for the MEMS switch state and the tunable laserhat optically controls the SOA-MZI. The MG-OXComprises a low cost, commercial, high-dimension,low 2D MEMS switch �10 ms� and a high cost, low-imension but fast �1 ns� SOA-MZI-based switch. Fig-re 12(a) illustrates the functional blocks of the test-ed, including the parallel [Fig. 12(b)], and sequentialFig. 12(c)] switch architectures. The egress node de-ects incoming bursts and can measure the BER of in-ividual bursts, based on the appropriate control (gat-ng) signals generated by an FPGA. The noderocessor integrates a CDR mechanism, a WAU, asell as a header processing (HP) unit. When an in-

oming BCH is received, the HP unit extracts theeader length, offset, and burst length and provides aignal (envelope) used to gate the BER test equipmentor the duration of the received burst. Finally, the con-rol plane is based on just in time (JIT) signaling andperates out-of-band in a full duplex mode at.5 Gbps.

. Control and Data Plane Implementation

Figure 13 shows the testbed architecture and ex-erimental setup. The OBS testbed operates at.5 Gbps for the control plane and 10 and 40 Gbps forhe data plane. All routers utilize a Xilinx high-speednd high-density VirtexII-Pro FPGA with an embed-ed PowerPC processor. The OBS control channel isull duplex (to allow synchronization) for both linksnd is transmitted on dedicated wavelength channelssing the proprietary Optical Burst Ethernetwitched (OBES) transport protocol [29]. The datalane transports variable sized bursts with variable

TABLE VBURST CONTROL HEADER (BCH) FORMAT

urst Header CoS Burst Offset Burst Src. Dest.

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time intervals on burst mode. The electronic section ofthe ingress edge router incorporates a differentiationscheduler (DS), classification scheduler (CS), wave-length allocation scheduler (WAS), and BCH assemblyand assignment. Burst generation is performed bycontrolling two 10 Gbps PPGs that generate the emu-lated bursts carrying 27−1 pseudo random binary se-quences (PRBS). The control signals for the bursts areenvelope patterns with variable duration and time in-tervals and are generated via the Rocket IO interfaceof the FPGA to gate the PPGs. The output from one ofthe two PPGs is used to externally modulate an opti-cal carrier at �5=1553.00 nm from a DFB laser usinga Mach–Zehnder modulator (MZM) producing the10 Gbps NRZ burst data stream. The second PPGmodulates a 10 GHz optical pulse stream (1.4 psFWHM, sech2-shaped pulse) from a tunable mode-locked laser (TMML) at �6=1556.65 nm, generating a10 Gbps RZ burst data stream. Further, the bursts aretime-multiplexed to 40 Gbps through a two-stage op-tical multiplexer (OMUX) that maintains the 27−1randomness. At the output of the ingress node, the 10

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nd 40 Gbps burst data streams are coupled andransmitted over a single fiber. In parallel to the datalane, the edge router generates and optically trans-its the BCH at 2.5 Gbps on an out-of-band wave-

ength ��2=1543 nm� towards the core router control-er. A second out-of-band control channel at �11544 nm is generated by the core router and re-eived at the ingress node to establish the full duplexontrol operation. A delay element inside the FPGA athe ingress node is used to synchronize the data planend control plane, by providing the appropriate offsetime between the BCH and data burst. The actualalue of the offset time is based on known propagationelays in the system and processing delays in the coreouter.The core router integrates an FPGA, a MEMS

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CDR, a WAU, as well as an HP unit. It should benoted that the switch is dynamically configured by theFPGA controller, which performs on-the-fly processingof the incoming BCH header information. According toCoS, offset, burst length, wavelength, and destination,the FPGA provides the appropriate electronic controlsignals for the MEMS switch state (for slow switch-ing), and the appropriate tuning sequences for thetunable laser that optically controls and configuresthe SOA-MZI (for fast switching). The MEMS switchis configured to have some soft-permanent dedicatedcross-connections in order to direct the small and me-dium sized bursts towards the SOA-MZI [see Figs.12(b) and 12(c)]. At the SOA-MZI switch, fast switch-ing of the shorter bursts between the bar and cross-bar state of the switch is achieved based on the exis-tence of a control wavelength from the tunable laserand the temporal position of this control. The SOA-MZI operation is based on standard switching inter-ference when a wavelength is applied to one of the twoSOA modules. Finally, the controller reinserts a newBCH for the next node. The combination of slow andfast switch is wavelength selective and can effectivelysupport OCS, OBS, or even OPS.

Finally at the egress side, the node integrates—similar to the core router—the CDR, WAU, and HPunits. The control plane is realized for duplex opera-tion (between the core router and edge router 2) without-of-band control channels at �3=1541.3 nm and �4=1547.4 nm for the two directions, respectively. Afterthe arrival of a BCH on the control channel, the ex-tracted (by the HP unit) information about the offsetand the burst length is processed and the appropriateburst envelope is generated and fed to the BER testerfor direct BER measurements on the burst level. Onthe data plane, the 10 Gbps burst data are detectedwith a pre-amplified receiver, while the 40 Gbpsbursts are first demultiplexed to 10 Gbps by means ofan electro-absorption modulator (EAM) and thenpassed to the pre-amplified receiver. In practice, aslightly shorter envelope of the exact burst length isused to gate the BER tester, in order to ease synchro-nization between the BER tester and the receivedburst.

B. Experimental Results

For the experimental evaluation of the MG-OXC,the OBS testbed described above is used to demon-strate dynamic controlled switching of variable-lengthoptical bursts (from 200 ns up to 30 ms) transmittedat 10 Gbps over �5=1553.00 nm and 40 Gbps over �6=1556.65 nm. The 40 Gbps data stream carries small-and medium-sized bursts (200 ns, 3.6 s, 5 s), whichare passed through the pre-configured MEMS to theSOA-MZI for fast switching. The 10 Gbps data streamcan be considered as long bursts or short circuits

30 ms� and is switched by the MEMS. In parallel tohese data bursts, the appropriate BCH is generatedy the ingress node and transmitted to the core router,hich in turn controls the MEMS and the SOA-MZI

via the tunable laser). Figure 14(b) shows the 3.6 song control signal on �7=1538.94 nm from the tun-ble laser that controls the SOA-MZI, and the result-ng switched bursts at both output ports for the cross-ar switching state. Another burst is switched using as long control signal on �8=1542.17 nm [Fig.

4(c)]. Figure 14(d) shows the 200 ns control signal on9=1548 nm and the switched bursts on both outputorts. The SOA-MZI gate is biased at the saturatedoint and configured to achieve the maximum staticxtinction ratio between the two output ports at anperating current of 354 and 360 mA for both SOAs,espectively. The configuration is based on a counter-ropagating set-up between the data and the controlignals while a holding beam is used (co-propagatingith data) in order to reduce the noise output of theOAs and improve the functionality of the gate forursty switching.

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BER measurements of the fast switched bursts at40 Gbps through the controllable SOA-MZI switchhave been obtained on the burst level after rate de-multiplexing with an EAM. The results (Fig. 15) showan acceptable penalty for this type of fast switch thatvaries between 1 and 2.2 dB for all the studied cases;these are the four possible bar and cross-bar switchingstates and for both control signals at �7 and �8. BERmeasurements at the output port of the MEMS switchrevealed a negligible penalty for both the 10 and40 Gbps burst data streams, implying that signalquality is not affected by the slow switch fabric. So theoverall performance of the MG-OXC is independent ofthe relative connectivity of the fast switch element(SOA-MZI) to the MEMS switch element. So both se-quential and parallel MG-OXC architectures have thesame physical layer performance.

It is also noteworthy that the utilized SOA-MZI-based set-up for fast switching is polarization sensi-tive. The optimization of polarization controllers andthe dynamic extinction ratio of the switch is done onlyonce for the control signal on �7 at switching port 2and maintained for all other cases. This is the reasonwhy this particular case shows better BER perfor-mance (1 dB penalty) compared to the other threecases (up to 2.2 dB penalty).

In this experiment, the main purpose was to suc-cessfully demonstrate the functionality of a multi-granular switch able to operate at multiple bit rates inan application-aware mode, defined by the appropri-ate control messages generated at the ingress nodeand processed at the core and egress router. For thisreason, a simple type of fast switch has been chosenwith certain known limitations. However, the intrinsicoperating flexibility of the multi-granular OBS set-uppresented here, as well as the flexibility in the nodearchitecture, allows the implementation of different

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ypes of fast switching set-ups, as the control signalsre generated from the core router processor and cane easily adjusted to any switching type. In this sense,olarization insensitive switching types [30,31] orven regenerative switching schemes [32,33] can bepplied, offering superior performance in terms ofER and better stability almost independent of the in-ut signals. Additionally, the use of the fast tunableaser-based controller at the core router allows thedoption of wavelength conversion schemes either forwitching (through passive routing via AWGs) or forontention resolution purposes [33]. The utilized tun-ble laser is capable of switching between 85 differentavelengths in less than 100 ns and with a maximumeak power difference of only 0.5 dB.

VI. CONCLUSIONS

Existing and emerging applications require dy-amic optical networks able to support different traf-c profiles with different levels of QoS (e.g., latency,

oss). Simultaneously, technologies like OCS, OBS,nd OPS seek flexible and agile combinations of wave-ength and sub-wavelength granularity for switchingnd routing of circuits, packets, and bursts directly inhe optical layer. MG-OXC is able to realize all men-ioned functionality by employing a flexible and scal-ble combination of relatively simple, low-cost, andigh-dimension optical switching fabrics with milli-econd switching speeds and low-dimension and ex-ensive switch elements with fast switching speeds.his paper presented the design and node-level analy-is of MG-OXCs. Furthermore, simulation analysisas used to evaluate a number of important param-ters concerning traffic load and switch design. Re-ults indicate that a MG-OXC with a limited numberf fast ports has similar performance to a design thatonsist solely of fast ports. Finally, we demonstratedhe feasibility of this architecture on an application-ware multi-bit-rate end-to-end OBS testbed. The de-loyed hardware consisted of a low-cost, commercial,igh-dimension, slow 2D MEMS switch �10 ms� and aigh-cost, low-dimension but fast �1 ns� SOA-MZIased switch.

ACKNOWLEDGMENT

he work described in this paper was carried out withhe support of the BONE-project (“Building the Fu-ure Optical Network in Europe”), a Network of Excel-ence funded by the European Commission throughhe 7th ICT-Framework Programme as well as a bilat-ral project funded by GSRT, Greece, and the Britishouncil called Autonomous Optical Networks for Glo-al Grid Computing Applications. M. De Leenheer isunded by the IWT through a Ph.D grant, and C.


Develder is supported by the FWO through a post-docgrant.

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Georgios S. Zervas was awarded theM.Eng. degree in electronic and telecommu-nication systems engineering with distinc-tion from the University of Essex (UK). Heis currently working towards the Ph.D. de-gree in optical networks for grid applicationand services at the University of Essex. Heis a Senior Research Officer in the PhotonicNetworks Lab at the University of Essex in-volved in the EC funded projects MUFINS,e-Photon/ONe�, Phosphorus, and BONE.

He is the author and co-author of over 40 papers in internationaljournals and conferences. His research interests include high-speedoptoelectronic router design, optical burst switched networks, GM-PLS networks, and grid networks. He is also involved in standard-ization activities in the Open Grid Forum (OGF) through the GridHigh Performance Networking Research Group (GHPN-RG) andthe Network Service Interface Working Group (NSI-WG).

Marc De Leenheer received the M.Sc. de-gree and Ph.D. in computer science engi-neering from Ghent University, Belgium, inJune 2003 and Dec. 2008, respectively. Heis currently a Post-Doctoral Researcher atthe same institution. His main interests in-clude modeling and optimization of gridmanagement architectures, specifically inthe context of photonic networks. He is in-volved in multiple national and Europeanresearch projects (IST Phosphorus, IST

e-Photon/ONe�, IST BONE). He is the author or co-author of over40 publications in peer-reviewed journals or international confer-ence proceedings.

Lida Sadeghioon received the B.S degreein electronic system engineering from Te-hran Azad University (Iran) in 1998 and theM.Sc. degree in computer and informationnetworks from the University of Essex (UK)in 2005. From 1999 to 2004 she was a Net-work Design Engineer for the Telecommuni-cation Company of Tehran. From 2005 to2007 she was a Research Officer for the Eu-ropean funded project MUFINS. She is cur-rently perusing a Ph.D. degree on all optical

signal processing for high speed optical networks at the Universityof Essex. Her research interest includes optical signal processing,WDM optical networks, and resource allocation and routing proto-cols for optical networks.

Dimitris Klonidis is an Assistant Profes-sor at Athens Information Technology Cen-tre, Greece. He was awarded his Ph.D. de-gree in the field of optical communicationsand networking from the University of Es-sex, UK, in 2006. In September 2005, hejoined the high-speed Networks and OpticalCommunications (NOC) group in AIT as afaculty member and Senior Researcher. Dr.Klonidis has several years of research anddevelopment experience, working on a large

number of national and European projects in the field of opticalswitching, networking, and transmission. He has more than 50 pub-lications in international journals and refereed major conferences.His main research interests are in the area of optical communica-tion networks, including optical transmission and modulation, sig-nal processing and equalization, and fast switching and node con-trol. The considered networking applications include future accessnetworks, and optical packet/burst switched networks.

Yixuan Qin received his M.Sc. degree incomputer and information networks fromthe University of Essex, Colchester, UK, in2003, where he is currently working to-wards his Ph.D. degree. Meanwhile he is aSenior Research Officer in the PhotonicNetworks Lab. His research interests in-clude high-speed digital system design, flex-ible networks, passive optical networks, op-tical burst switching, and high performancehardware accelerated computing.

Reza Nejabati joined the University of Es-sex in 2002, and he is currently a member ofthe Photonic Network Group at the Univer-sity of Essex. During the last 8 years he hasworked on ultra high-speed optical net-works, service oriented and application-aware networks, network service virtualiza-tion, control and management of opticalnetworks, and high-performance networkarchitecture and technologies for e-science.He holds a Ph.D. in optical networks and an

.Sc. with distinction in telecommunication and information sys-ems.

Dimitra Simeonidou is currently a Pro-fessor at the University of Essex. She hasover 10 years experience in the field of opti-cal transmission and optical networks. In1987 and 1989 she received a B.Sc. andM.Sc. from the Physics Department of theAristotle University of Thessalonica,Greece, and in 1994 a Ph.D. degree from theUniversity of Essex. From 1992 to 1994 shewas employed as a Senior Research Officerat the University of Essex in association

ith the MWTN RACE project. In 1994 she joined Alcatel Subma-ine Networks as a Principle Engineer and contributed to the intro-uction of WDM technologies in submerged photonic networks. Shearticipated in standardization committees and was an advisingember of the Alcatel Submarine Networks patent committee. Pro-

essor Simeonidou is the author over 250 papers and holds 18 pat-nts relating to photonic technologies and networks. Her main re-earch interests include optical wavelength and packet switchedetworks, network control and management, and GRID network-

ng.

Chris Develder received the M.Sc. degreein computer science engineering and aPh.D. in electrical engineering from GhentUniversity (Ghent, Belgium), in July 1999and December 2003, respectively. From Oc-tober 1999 on, he worked in the Depart-ment of Information Technology (INTEC),at the same university, as a Researcher forthe Research Foundation–Flanders (FWO),in the field of network design and planning,mainly focusing on optical packet switched

etworks. In January 2004, he left the university to join OPNETechnologies, working on transport network design and planning.n September 2005, he re-joined INTEC at Ghent University as aost-Doctoral Researcher, and as a Post-Doctoral Fellow of theWO since October 2006. Since October 2007 he has held a Part-ime Professor position at the same institute. He was and is in-olved in multiple national and European research projects (ISTion, IST David, IST Stolas, IST Phosphorus, IST e-Photon One).is current research focuses on dimensioning, modeling, and opti-izing optical grid networks and their control and management. He

s an author or co-author of over 45 international publications.

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Bart Dhoedt received a degree in engi-neering from the Ghent University in 1990.In September 1990, he joined the Depart-ment of Information Technology of the Fac-ulty of Applied Sciences, University of Gh-ent. His research, addressing the use ofmicro-optics to realize parallel free spaceoptical interconnects, resulted in a Ph.D.degree in 1995. After a 2 year post-doc inopto-electronics, he became a Professor atthe Faculty of Applied Sciences, Depart-

ment of Information Technology. Since then, he has been respon-sible for several courses on algorithms, programming, and softwaredevelopment. His research interests are software engineering andmobile and wireless communications. He is the author or co-authorof approximately 150 papers published in international journals orin the proceedings of international conferences. His current re-
search addresses software technologies for communication net-
orks, peer-to-peer networks, mobile networks, and active net-orks.

Piet Demeester received his Ph.D. degree(1988) at Ghent University, where he be-came a Professor in 1993. He is heading aresearch group on broadband communica-tion networks and distributed software:www.ibcn.intec.ugent.be. His current re-search interests include multilayer net-works, quality of service mobile and sensornetworks, access networks, grid computing,energy efficient ICT, distributed software,network and service management, and

echno-economics and applications. He is co-author of over 700 pub-ications in international journals or conference proceedings.

Documents

Multi-Granular Optical Cross-Connect: Design, Analysis