Considering the Impact of Transmission Impairments on the Performance of Dynamic Traffic Grooming

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1 Considering the Impact of Transmission Impairments on the Performance of Dynamic Traffic Grooming by Géza Geleji Submitted to the Department of Electrical Engineering and Information Technology in partial fulfillment of the requirements for the degree of Diploma in Information Technology at the BUDAPEST UNIVERSITY OF TECHNOLOGY AND ECONOMICS May 2007 Advisors: Dr. Tibor Cinkler, Associate Professor Péter Hegyi, Doctor of Philosophy student Szilárd Zsigmond, Doctor of Philosophy student Department of Telecommunications and Media Informatics Budapest University of Technology and Economics

2 Contents Abstract Kivonat Introduction Communication Networks Switching Packet Switching Circuit Switching Burst Switching Functional Grouping of Network Elements Automated Provisioning Layered Network Reference Models The OSI and the TCP/IP Layered Network Reference Models Protocol Stacks Horizontal Network Partitioning Fiber-Optic Communication Devices Overview of the Relevant Core Networking Principles & Technologies 18 2

3 2.1 Plesiochronous Digital Hierarchy (PDH) The Synchronous Optical Network (SONET) and the Synchronous Digital Hierarchy (SDH) Internet Protocol (IP) Quality of Service in IP Asynchronous Transfer Mode (ATM) Optical Time-Division Multiplexing Wavelength-Division Multiplexing SONET/SDH over WDM IP over WDM Multi-Protocol Label Switching (MPLS) MPLS-TE Generalized Multi-Protocol Label Switching (GMPLS) Multi-Region Networks Layer Inter-Operability Models for Vertical Integration Traffic Engineering The Automatically Switched Optical Network Transport Networks Wavelength-Routing Networks Routing and Wavelength Assignment Subrate Multiplexing and Traffic Grooming Next-Generation Networking

4 3 Modelling Signal Degradation in the Physical Layer Phenomena Affecting Optical Signal Quality in Large-Scale WR Networks Polarization-Mode Dispersion (PMD) Amplified Spontaneous Emission (ASE) Crosstalk (XT) Calculating the Q Factor Calculating Eye-Related Penalties Calculation of Noise-Related Penalties A Graph Model for Describing Subrate Multiplexed Wavelength-Routing Networks A High-Level Overview of Common Network Node Types Graphic Representation of Wavelength-Routing Networks Subrate Multiplexing Lightpaths Calls Traffic samples Observations in Routing Simulations The IDRSIM (Intra-Domain Routing) Simulator The Network Topology Descriptor Files Traffic Sample Files and Their Generation Modelling Signal Propagation in the Physical Layer

5 5.2 Simulation Parameters and Results Network and Traffic Parametrization Traffic Sample Dimensioning Results of Simulations with Physical Constraints Conclusions Appendix 75 Contents of the DVD Attachment About the Network Topologies Acknowledgements 80 Bibliography 81 5

6 Considering the Impact of Transmission Impairments on the Performance of Dynamic Traffic Grooming by Géza Geleji May 2007 Abstract Optical networking is still an emerging, but very promising possibility in telecommunications. Although it is widely employed in backbone networks, there are still many unexploited possibilites open for further research. The work presented herein wishes to deal with Dense Wavelength-Division Multiplexed Wavelength-Routing Mesh Networks (WR-DWDM), which is an all-optical switching technology suitable for arbitrary network topologies. A WR network in itself, as it can only switch complete wavelengths, is not appropriate for serving typical client connection demands. Such requests typically require bandwidths by orders of magnitude smaller than the capacity of a single wavelength channel. Therefore, we couple the WR-DWDM technology with traffic grooming; this enables the intelligent, on-line multiplexing of client connection requests into wavelength channels. Much attention has been paid to this dual technology in the recent years; its most attractive properties include outstanding versatility and scalability. However, we think that further research should be donated to disclose its shortcomings; we have chosen to address one of these, namely, the possible limitations caused by phenomena in the physical layer. In our work, after reviewing the set of technologies that have influenced our work, we will present a model suitable for simulating physical-layer phenomena, then a graph model for the description of dynamic traffic grooming in WR networks. We will see that analytical modelling is practically impossible for the type of networks investigated herein; as a consequence, we will resort to simulations as an apparatus for stating and proving our conclusions. 6

7 Considering the Impact of Transmission Impairments on the Performance of Dynamic Traffic Grooming készítette: Geleji Géza május Kivonat Az optikai hálózatok egy jelenleg is fejlődésben lévő, rendkívül ígéretes lehetőséget képeznek a távközlésben. Habár optikai gerinchálózatokat széles körben alkalmaznak, számos kihasználatlan lehetőség rejlik a témában további kutatás számára. Az itt bemutatott munka a sűrű hullámhossz-osztásos nyalábolás technológiájára épülő hullámhossz-kapcsolt hálózatokkal (WR-DWDM) kíván foglalkozni, amely egy tisztán optikai, tetszőleges hálózati topológia felett megvalósítható kapcsolási módszer. Mivel egy WR-DWDM hálózat csak teljes hullámhosszokat képes kapcsolni, önmagában nem alkalmas tipikus előfizetői igények kiszolgálására. Az ilyenek rendszerint nagyságrendekkel kisebb sávszélességet igényelnek, mint egyetlen hullámhosszcsatorna kapacitása. Emiatt a WR-DWDM technológiát forgalomkötegeléssel (traffic grooming) párosítjuk; ily módon lehetővé válik az előfizetői kapcsolatok intelligens, valós időben történő nyalábolása hullámhossz-csatornákba. E kettős technológia jelentős figyelmet kapott a közelmúlt években; legvonzóbb tulajdonságai közt említhetjük kiemelkedő rugalmasságát és skálázhatóságát. Mindezek ellenére úgy gondoljuk, további kutatásokra van szükség a technológia korlátainak felfedésére; úgy döntöttünk, hogy ezek közül a fizikai rétegben fellépő jelenségek által okozott korlátokat fogjuk megvizsgálni. Munkánkban, miután áttekintettük azon technológiákat, melyek a gondolatmeneteinket befolyásolták, bemutatunk egy lehetséges modellt a fizikai hatások kiszámítására, majd egy gráf-alapú modellt a WR-DWDM hálózatokban alkalmazott forgalomkötegelés reprezentálására. Látni fogjuk, hogy a tisztán analitikus modellezés gyakorlatilag kivitelezhetetlen a jelen műben vizsgált hálózattípusra; ennek következményeként szimulációhoz fogunk folyamodni következtetéseink levonása és igazolása érdekében. 7

8 Chapter 1 Introduction Telecommunication, according to ATIS [1], refers to any transmission, emission, or reception of signs, signals, writing, images and sounds or intelligence of any nature by wire, radio, optical or other electromagnetic systems. In the present state of the art, this translates to a vast range of potential fixed and mobile applications, including broadcasting, data transfer, hypertext transfer, telecommand, teleconferencing, tele-education (distance learning), telefax, telegraphy (text transfer), telemedicine, telemetry, telephony and television. These examples, though ambiguously, can be classified into, with respect to the relations between participating entities, three major groups: point-topoint, point-to-multipoint and broadcast communications. Point-to-point communication refers to the process of information exchange, either uni- or bidirectional, between two endpoints. In point-to-multipoint transfer, a central endpoint is capable of simultaneously communicating with a set of other endpoints; however, the members of this set might not necessarily be able to communicate with each other, and also, the central endpoint might not necessarily be able to address the others individually (that is, all members of the set receive the same information). Point-to-multipoint communication might also be either uni- or bidirectional, although realization of the bidirectional case requires certain considerations and is sometimes realized by means of point-to-point links. Broadcast communication refers to the case when a central endpoint broadcasts exactly the same information to a very large set of other endpoints simultaneously. The central endpoint can not distinguish between the members of the set and the information flow is almost always unidirectional. 8

9 The scope of our work is restricted to point-to-point communications; this is a direct consequence of the physical properties of the transmission medium we wish to investigate. Additionally, in theory, any communicational requirement, including the broadcast and multicast cases, can be satisfied using an appropriate set of point-topoint data links. However, in practice, careful planning is often required for effective realizations. 1.1 Communication Networks Let us consider a scenario where the members (arbitrary entities) of a large population are distributed throughout an extensive area and any member may wish to forward information to a different member at any time by the means of a point-topoint connection between the two members. Whenever member X wishes to transport information (the functional process of transferring information between different locations in space is referred to as transport [8]) to member Y at a transfer rate of r during the time interval [t, t + τ), we shall say that a communicational demand from X to Y has been born at t with duration and transfer rate of τ and r, respectively. If the population is infinite, the birth process of communicational demands will be a Poisson-process. It is easy to see that catering to the needs raised by this scenario requires careful planning. If every member of the population must be able to transmit information to every other member at the same time along the shortest possible single link, then the correct solution requires a full mesh of bidirectional point-to-point links, which would require laying cables (a) A fully connected 4 (b) A four-node tree four-node mesh Figure 1.1: Topology differences along straight lines between all pairs of members. In practice, fortunately, this requirement is unusual and far-fetched; accordingly, the proposed solution is wasteful and unnecessarily costly. Relaxing the constraint on link lengths, for example, will cause a significant reduction in costs along with a, usually, negligible degradation in 9

10 performance. If we allow point-to-point connections to span multiple links, the total number of links required can be greatly reduced. Figure 1.1(a) shows that a fully connected mesh of four nodes requires = 6 links, while a tree with the same number of nodes (Figure 1.1(b)) requires only 4 1 = 3. In the former case, a connection between any pair of nodes can be established through a single link; in the latter, connecting Node 2 to Node 4 requires two links. If any adverse phenomenon (power outage, network congestion, etc.) affects Node 1, it will also affect the communication between other nodes as well Node 1 is a single point of failure. Clearly, the full mesh provides a more reliable service at a higher cost; the tree is cheaper, though less reliable. This simple example already suggests that the arrangement of links can significantly affect the overall cost, reliability, and performance of the service. In the rest of this document, we will use the term network to denote such sets of nodes and links (note that this is already very different from the concept of network known from graph theory, but is closely related to the notion of graphs; a special kind of communication networks will be formalized in Section 4). Since extensive research is available on network topology [27, 28, 29], the study of arrangement of links and nodes in a network, we do not wish to delve into the rather complex details. The primary purpose of communication networks can be summarized in efficiently serving the communicational demands of a large community of users. Such networks may span several countries, whole continents (transcontinental networks) or even larger areas (intercontinental networks). The term communicational demand translates to a plethora of possible applications which were detailed in the first paragraph of the introduction. At their emergence, most of them were supported by their own, separate infrastructures; however, experience has proven that a common infrastructure would allow for a much more costefficient realization. For this reason, modern transport networks will be expected to support most of them. Different types of services impose different requirements on the transport infrastructure; e.g., voice telephony is much more sensitive to latency jitter than video-on-demand, but the latter requires a much higher data transfer rate. Providing adequate service to different applications co-existing on a single network is dealt with in the subject called Quality of Service [42, Chapter 59]. 10

11 1.2 Switching Originally, the term switching refers to The controlling or routing of signals in circuits to execute logical or arithmetic operations or to transmit data between specific points in a network. Note: Switching may be performed by electronic, optical, or electromechanical devices. [1] In the context of digital communications, this means the control of network elements in such a way that certain signals transported in the network are routed and forwarded from their source towards their intended destination. Two basic types of switching are distinguished according to the type and format of the routed signals Packet Switching In packet switching, all signals in the network are organized into packets, i.e. continuous sequences of bits. Packets usually contain client information and a header (supplementary information in a well-defined format added by the network). Elements of the network infrastructure may process portions of the packet in order to be able to forward it correctly (this is not necessary; separated control mechanisms are possible too) Circuit Switching Circuit switched networks are capable of creating a continuous circuit between two endpoints. Information sent along the circuit will not be altered by the network, except by the physical transmission impairments caused by the physical properties of the transmission media. In electronic digital transmission systems, this might mean the end-to-end preservation of the analog waveform, but it can also refer to the preservation of the digital logic value (high or low) of the signal only. Network components will not process the information being transmitted; switching control is the responsibility of a dedicated control plane (see Section 1.2.4). 11

12 Transparency In optical networks, it is possible to realize circuit switching in a way that the end-toend connection is made purely in the optical domain; that is, no optical-to-electronic or electronic-to-optical converters are used along the route. This solution strives to preserve the analog waveform of the optical signal entering at one endpoint of the connection; however, physical phenomena in fibers, switches and amplifiers might cause deterioration. The term transparent refers to the fact that an optical signal (which is, actually, modulated light) propagating along a transparent connection only encounters materials that allow it to pass through Burst Switching Burst switching is an emerging technology used in optical networking. As it switches very long streams of bits, it can be regarded as a transition between packet and circuit switching. Its discussion is outside the scope of this work; however, excellent literature is available on the topic in Perros s book [35, Chapter 10] Functional Grouping of Network Elements Modern literature on transport networks [8, 9, 16, 17] classifies the functional elements of the infrastructure into three distinct categories called planes: the transport, the control and the management planes (the term plane is intended to express the orthogonal being of this partitioning to the layering concept discussed in Section 1.3). According to G.8081 [17], The tranport plane provides bidirectional or unidirectional transfer of user information, from one location to another. It can also provide transfer of some control and network management information. The transport plane is layered; it is equivalent to the»transport Network«defined in ITU-T Rec. G.805 [8]. The control plane has several purposes, ranging from the efficient configuration of connections within a transport layer network to protection and restoration functions; these are detailed in G.8080 [16]. Finally, The management plane performs management functions for the transport plane, the control plane and the system as a whole. It also provides coordination between all the planes. The following management func- 12

13 tional areas identified in ITU-T Rec. M.3010 are performed in the management plane: performance management; fault management; configuration management; accounting management; security management. [17] Automated Provisioning In early core networks, the provisioning of client connections usually involved manual setup and teardown. In networks based on complex architectures, this was a slow, costly and error-prone task [74]. This raises an increased demand towards automated provisioning, where the processes in question are handled by a specialized control and management infrastructure [16, 17]. 1.3 Layered Network Reference Models The architectures of communication networks, especially those of the transport networks discussed above, can be quite complex. In order to facilitate their discussion, it is often helpful to organize network components into architectural layers that conform to the following principles: A layer is a group of functional elements that might provide services to other layers and might also take advantage of services provided by other layers. Other layers should not rely on the internal processes of a particular layer. Each layer can rely on the services provided by the immediate underlying layers in order to provide services to the layers immediately above, but can not use the functionality of other, not immediately adjacent, layers. Let s look at Figure 1.2(a) for an illustration of a network layering: in this example, layer A can explicitly use the services of layers B1 and B2 through the so-called Service Access Points of B1 and B2, but can not explicitly access those of layer C (only through the services provided by B1 and B2). The relationships between A, B1 and B2 can be described by saying that A is a client of B1 and B2; B1 and B2 are servers of A. A 13

14 Application Presentation IP Session Application GTP Transport Transport UDP IP A Network Network IP MPLS B1 B2 Data Link Data Link L2 ATM C Physical Physical L1 L1 (a) Layer diagram (b) The ISO OSI (c) The TCP/IP (d) The GPRS (e) IP/MPLS/ATM of a general net- reference model reference model Tunneling Pro- work architecture tocol in the GGSN Figure 1.2: Examples of Network Layering and B1, A and B2, B1 and C, as well as B2 and C, are in client-server relationships. B1 and B2 are practically unrelated to each other: both provide services to A and both might use the services of C, but they can t inter-operate with each other. We shall call B1 and B2 parallel layers. The type of diagram presented on Figure 1.2(a) can not represent all imaginable relationships among sets of layers, but it can represent most practical possibilities. We will see that this layering concept can be applied to various structural partitionings of communication networks The OSI and the TCP/IP Layered Network Reference Models With the original purpose of facilitating interconnection between systems, ISO/IEC defined a layered reference model, OSI (Open Systems Interconnection) [21], in which network components were grouped into seven individual layers with respect to their functionality: Physical, Data Link, Network, Transport, Session, Presentation and Application (see Figure 1.2(b)). DARPA has created a similar model consisting of four layers several years earlier. The DARPA model has been extended to five layers and is now often referred to as the TCP/IP reference model (see Figure 1.2(c)). 14

15 1.3.2 Protocol Stacks Many network architectures are compatible with the OSI and TCP/IP type of layering and the principle has been of fundamental importance ever since its introduction. However, very often, it is more convenient to use layers to represent and correspond to individual network protocols; such representations, which are often called protocol stacks, might not be entirely compatible with the OSI or the TCP/IP structure. As an example, let us consider a protocol stack snatched from the Gateway GPRS Support Node of a GPRS (General Packet Radio Service) network [76], as can be seen on Figure 1.2(d); it is interesting to note that the Internet Prototocol is present in two instances. According to ISO [21], The Network Layer provides the functional and procedural means for connectionless-mode or connection-mode transmission among transportentities and, therefore, provides to the transport-entities independence of routing and relay considerations. This matches the functionality of IP in general and that of the lower instance, but what about the topmost IP layer? If there are no functional differences between the two IP layers, why would they correspond to different OSI or TCP/IP layers? Also, a glance at the example of Figure 1.2(e) raises another question: if L1, ATM and IP are responsible for providing the functionality of, respectively, the Physical, the Data Link and the Network layers, which OSI layer does MPLS correspond to? What s more, the capabilities of ATM span several OSI and TCP/IP layers. It is obvious that a one-to-one correspondence between protocol stacks and the layers of the OSI or TCP/IP reference models is not always possible. For this reason, in the rest of this document, we will use the term layer as a reference to an element of a protocol stack, as on Figures 1.2(d) and 1.2(e), and not as a reference to a layer of the OSI or TCP/IP reference models Horizontal Network Partitioning In additioning to the vertical layering concept discussed above, ITU-T has defined a way of partitioning large-scale networks horizontally into administrative domains and subnetworks [8, Section 5.3]. This subdivision serves a complex purpose [8, Section ]: it separates the administrative and routing areas of different network operators providing services over the same network; it also enhances network scalability 15

16 by encouraging the use of hierarchical (inter-domain) routing procedures. Networks comprising multiple administrative domains are referred to simply as multi-domain networks. 1.4 Fiber-Optic Communication Devices The discovery that an appropriately doped, thin strand of silica acts as a waveguide [35, Section 8.2] in a certain domain of the electromagnetic spectrum has had a fundamental impact on digital communications in the late 1970s. Since silica (SiO 2 ) is available in abundant quantities (as opposed to materials used in electric trasmission lines; note that both Si and O are among the ten most common elements in the universe and they are the two most common elements in the Earth s upper continental crust and for every 10 6 atoms of Si, there are only approximately 30 corresponding atoms of copper [22]) and efficient means of fiber manufacturing are available, the potential cost of the optical fiber is low. In addition, fiber-optic devices outperform conventional transmission media, like electronic cables or radio waves, in terms of reliability and data transfer rate. Signals through optical fibers are transmitted using electromagnetic waves of wavelengths between 1260 and 1625 nanometers (the attenuation of the transmitted signal is the lowest in this range in moder fibers; the Handbook of Optical Communication Networks gives examples of the spectral attenuation properties of modern fibers [45, figures 1.3 and 19.3]). The propagation characteristics of this domain in lightguides allow the very efficient shielding of the transported signal from external sources of interference; conversely, the interference caused by the signal itself (including crosstalk between fibers) is negligible as well. These advantages allow a favorable bit-error rate (as low as in practical applications) for data transfer. The useful bandwidth of a single strand of fiber can be measured in tens of THz, which is significantly higher than that of most other media. As a consequence, one can be fairly sure that fiber optic communication will be a dominant technology in the upcoming decades. Taking full advantage of the bandwidth provided by silica fibers poses certain challenges that must be dealt with. Allocating the whole bandwidth to a single digital data stream would require a bit transfer rate of about 50 terabits per second, which is 16

17 currently too fast for semiconductor switching devices to handle. Transmitters used to produce the optical carriers are mostly built using Light Emitting Diodes (LEDs), Edge-Emitting Semiconductor Laser Diodes or Vertical Cavity Surface-Emitting Lasers (VCSELs) [49, Chapter 2] [50, Chapter 5] [51, Chapter 3]. LED devices have large rise times that limit their modulation response bandwidth to less than 200 MHz; this value increases to a few GHz for edge-emitting semiconductor lasers and near 50 GHz for VCSELs. These modulation rates are, at best, a thousand times smaller than the bandwidth of the optic fiber; this implies that electronic TDM (Time-Division Multiplexing) methods cannot be used to fully exploit the available resources and some form of multiplexing is required in the optical domain. The most promising candidates are the OTDM (Optical Time-Division Multiplexing) and WDM (Wavelength- Division Multiplexing) technologies [35, Section 8.1] [45, Chapter 19] [46, Chapter 2]. These techniques will be discussed later in Sections 2.5 and

18 Chapter 2 Overview of the Relevant Core Networking Principles & Technologies 2.1 Plesiochronous Digital Hierarchy (PDH) PDH is a hierarchical TDM (Time Division Multiplexing) scheme proposed for multiplexing PCM-encoded telephone lines [80, Section 1.1] [35, Section 2.1] [34, Section 2.4] [35, Section 2.1] [4]. It consists of approximately 6 multiplexing levels (there were different realizations in North America and Europe) that correspond to specific data rates; on each level, a given number of signals can be multiplexed from the underlying level in order to form a single, aggregate signal. The name plesiochronous refers to the fact that the signals being multiplexed need not be exactly synchronous, i.e., a slight dissimilarity between the transfer rates is allowed. To achieve the synchrony required for the generation of the aggregate signal, multiplexers employ a technique called bit stuffing [34, Section 2.3.4]. Unfortunately, it is not possible to mix signals from different levels: on level k, one can only multiplex a pre-defined number of k 1-level signals (the converse applies to demultiplexing). This restriction makes switching equipment unnecessarily complex, and, along with the low possible data transfer rates, encumbers the use of PDH in modern data networking applications. 18

19 2.2 The Synchronous Optical Network (SONET) and the Synchronous Digital Hierarchy (SDH) SONET (North America) and SDH (elsewhere) were designed, respectively, by Telcordia [20] and ITU-T [5, 6, 7] as replacements and extensions to their respective PDH T1/E1 counterparts. They are capable of multiplexing top-level PDH signals in additional hierarchical levels in exact synchrony up to aggregate data rates of approximately 40 Gbits/sec using fiber optic media in the physical layer [35, Chapter 2] [34] [36, Chapters 2 and 3] [49, Section 12.2] [50, Section 8.6]. SONET/SDH signals are formed by the periodic, synchronous transmission of frames conforming to pre-defined formats, which are discussed in detail by Perros [35, Chapter 2]. Their synchronous nature allows for the simple realization of a wide range of devices, such as terminal multiplexers, add-drop multiplexers and digital cross-connect systems [35, Chapter 2]. These devices allow the creation and interconnection of selfhealing rings, which add a certain level of survivability to the network by the means of link protection. The Generic Framing Procedure (GFP) introduced in G.7041 [11] is capable of delineating variable-length, byte-aligned client payloads into SONET/SDH frames, allowing a wide range of (but not all) client protocols to be used over SONET/SDH. It also supports the propagation of Operation and Maintenance information and includes an error detection mechanism that protects the headers and the payload. The Next Generation SONET/SDH architecture uses GFP, Virtual Concatenation (VCAT) and Link Capacity Adjustment Scheme (LCAS) to allow SONET/SDH to be used as a flexible, integrated transport network [37] [35, Section 2.8] [39]. It is easy to see that SONET/SDH is a simple, yet universal transport solution that can be used to support a wide range of clients, including, but not limited to IP, ATM and Ethernet. Unfortunately, in its present state, it can not fully utilize the bandwidth of fiber optics. Its client data rate granularity (see Section ) is high: clients can only be allocated channels with data rates that are multiples of STS-1, which corresponds to approximately 50 Mbits/sec. Furthermore, the SONET/SDH standards only define operation on a limited set of network topology types (linear, ring and interconnected 19

20 rings) [41] which might prove to be a hindrance of further scalability. 2.3 Internet Protocol (IP) The Internet Protocol is a very versatile data-oriented protocol for packet-switched digital communications. Since it is quite widely used, much research is being conducted about providing various services over IP networks and, conversely, about realizing the Internet Protocol on different types of network infrastructures. Due to this, IP is often considered a convergence layer [44, Chapter 18], that is, a protocol which makes communication services independent of the underlying network infrastructure and creates the potential for realizing any combination of infrastructure and service in the same network. It does not protect against client data corruption, packets arriving out of order, packet duplication and loss; these simplifications reduce the processing demands on IP routers, although they encumber the provision of guaranteed-quality services. In spite of the shortcomings, IP is still suitable for a wide range of potential applications and many predict IP to become a dominant networking technology in the next decades [62, Section 11.1] Quality of Service in IP The shortcomings of IP can be summarized by saying that IP provides a best effort service, that is, important network services rely on greedy algorithms that often produce sub-optimal solutions, most commonly in complex scenarios. Two important architecures have been proposed to overcome thes limitations: Integrated Services (IntServ) [77] [79, Section 12.2] [62, Section 11.2] and Differentiated Services (DiffServ) [78] [79, Section 12.3] [62, Section 11.3]. IntServ provides best effort service, real-time (guaranteed and predictive) service (by employing resource reservation and admission control) and controlled link sharing (controlled bandwidth sharing by traffic classes on links). It does not scale well to large networks and this was the main reason behind the development of DiffServ, which relies on traffic classification (instead of per-flow control) to achieve different per-hop behaviors for different types of traffic in IP networks. Unlike IntServ, DiffServ needs to be provisioned and there is no 20

21 differentiation between flows belonging to the same traffic class. Other important challanges include billing and monitoring. The greatest drawback that is common to IntServ and DiffServ is that provisioning is separated from routing, therefore it is possible that a traffic flow will not be admitted to a network which otherwise has the necessary amount of free resources [38]. 2.4 Asynchronous Transfer Mode (ATM) Since its standardization by ITU-T in 1987, ATM [35, Chapters 3-5] [42, Chapter 31] [81] [49, Section 12.3] has become an extensively used cell relay protocol in Wide Area Networks and Access Networks; also, most modern mobile telephony infrastructures are based on ATM [75]. It was designed for the simultaneous transmission of voice, video and data (primarily, but not exclusively) in fiber-optic networks; transmission rates range from the order of a few Mbits/sec to several Gbits/sec. A fixed cell size of 53 bytes ensures low forwarding delays and jitter, which is ideal for video and voice transmission. Unlike IP, it provides a predictable service through resource reservation and point-to-point connections; the inherent support of Quality of Service is based on the classification of traffic flows into six categories (constant bit rate, realtime variable bit rate, non-real-time variable bit rate, available bit rate, unspecified bit rate and guaranteed frame rate). Resource provisioning is realized by admission control; internal nodes do not control individual flows. Since ATM was designed for highly reliable transmission media, client data is not protected from transmission errors. Perhaps the most severe limitations of ATM is its limited performace and the fact that it is not being used for what it was originally planned for: most of its capabilities remain unexploited in common applications. For a list of ATM-related ITU-T recommendations, refer to ITU-T I.326 [18]. 2.5 Optical Time-Division Multiplexing OTDM is the realization of TDM by means of all-optical devices [45, Section ] [46, Chapter 2] [73, Section 8.6]. Currently, its practical applications are limited by the 21

22 fact that present technologies limit the aggregate data transfer rate to approximately 250 Gbits/sec. However, this speed is sufficient for OTDM to be employed in subrate multiplexing (refer to Section ) schemes. 2.6 Wavelength-Division Multiplexing WDM [46] [48, Chapters 1, 16] is basically an analogy of Frequency Division Multiplexing Band Name Domain (nm) in the infra-red domain; it involves, on O (Original) the transmitter side, the generation and multiplexing E (Extended) of several, bandwidth-limited and S (Short) spectrally disjoint optical signals into a single C (Conventional) fiber. The signals can be produced by L (Long) LASER devices and multiplexing in itself does not pose a significant challenge [51, Section U (Ultra-Long) ]. On the receiver side, the individ- Table 2.1: Wavebands in Optical Fibers ual signals should be separated (demultiplexed), and converted to electronic signals using appropriate optical signal detectors. Demultiplexing is mostly done by diffraction-based demultiplexers or interference-based demultiplexers [51, Section 8.2.2]; one of the most promising approaches seems to be the Arrayed Waveguide Grating [51, Sections and 8.2.5]. Literature distinguishes dense and coarse WDM technologies depending on the spacing of the wavelength channels: the Dense WDM (DWDM) recommendation described in ITU-T G694.1 [2] supports channel spacing values of 100, 50, 25 and 12.5 GHz with, respectively, approximately 115, 229, 458 and 916 channels in the C and L bands (see Table 2.1) [45, Section ]; the Coarse WDM (CWDM) scheme (ITU-T G694.2 [3]) defines 18 channels with channels spacings larger than 2 THz in the spectral bands designated by the letters O, E, S, C and L. When used without a density specifier, the term WDM generally refers to the dense channel spacing scheme; we will resort to this convention in our work as well. In Section 1.4, we have said that the noise caused by crosstalk between individual optical fibers is negligible. Unfortunately, the same is not true for wavelength channels in the same fiber: several phenomena are responsible for the significant amount 22

23 of crosstalk possible in WDM systems, including heterowavelength linear crosstalk [51, Section 8.3.1], homowavelength linear crosstalk [51, Section 8.3.2], nonlinear Raman crosstalk [51, Section 8.3.3], stimulated Brillouin scattering [51, Section 8.3.4], cross-phase modulation [51, Section 8.3.5] and four-wave mixing [51, Section 8.3.6] SONET/SDH over WDM As the original SONET/SDH design was planned to be compatible with WDM [10, Section 6.1], significant research has been devoted to the issues about efficiently deploying SONET/SDH over WDM [68] [69] [70] [71] [72] [82] [83] [84]. In a linear or ring SONET/SDH network, additional parallel channels can be included by supporting them on new wavelengths in the underlying WDM infrastructure, therefore, no additional fibers are required. While accommodating a given set of calls (see Section 4.3), the two most important measures that should be minimized are the number of parallel SONET/SDH rings and the number of SONET/SDH add/drop multiplexers (refer to Section 4.1) used. It has been shown that minimizing either of the variables might result in the other being non-minimal and, therefore, joint optimization methods are required. The problem of allocating network resources to a given set of calls has been referred to as the traffic grooming problem [43, Section 1.2, Chapter 8]; it comprises a wide range of optimization problems, many of which have been proven to be NP-complete (e.g., minimizing the number of wavelengths used in a SONET-over- WDM ring network is Karp reducible to the bin packing problem). Quite obviously, these problems can be generalized to WDM mesh networks as well [44, Chapter 9] IP over WDM As it was mentioned earlier, IP is expected to become a dominant networking protocol in the near future; much research is being devoted to providing various services over IP networks [62, Chapter 2]; also, IP has been extensively tested as a network protocol on the Internet. Quite clearly, the WDM technology is capable of providing the networking infrastructure required by the vast amount of expected IP traffic. IP s potential role as a convergence layer and WDM s abundance of physical resources 23

24 makes the IP/WDM combination a favorable possibility in tomorrow s backbone networks [44, Chapter 18] [85]. The most obvious problem about this pairing rises from the profound differences between the two components: as WDM is a physical-layer solution and IP is a packetrelay networking protocol, any realization requires one or more intermediate adaptation components. In practice, such realizations are easily imaginable by using a large number of intermediate layers (see Figure 2.1(a)), such as SONET, ATM, etc. However, as the IP Frame Relay (a) The ATM SONET DWDM conventional approach IP IP/DWDM Adaptation Layer DWDM (b) A simplified solution Figure 2.1: IP over DWDM multitude of such layers will likely result in the inefficient usage of both bandwidth and processing resources, impaired scalability and unnecessary complexity of design, deployment and maintenance [53] [63] [66], one might desire an architecture with a minimal number of layers (Figure 2.1(b)) with well-defined inter-operability in between, so that the possibility of optimal resource usage is left open [48, Chapter 13 Section 3.1.1, Chapter 16 Section 1.1]. One of the most important unsolved issues is the design of efficient co-operation between the IP and WDM layers [46, Section 8.6.2]. The control plane architectures discussed in Sections 2.8 and 2.9 are suitable for resolving the DWDM control issues in this challenge. 2.7 Multi-Protocol Label Switching (MPLS) MPLS [57] [60] is a packet-forwarding protocol designed for high performance applications in mesh networks. It imposes very few requirements on the client layer and minimal processing demands on the forwarding equipment. MPLS is often considered as a candidate in the IP/WDM inter-operation issue presented above. 24

25 2.7.1 MPLS-TE MPLS supports traffic engineering (see Section 2.8.3) by being able to define arbitrary paths for network flows through the use of Label Distribution Protocols [58]. MPLS clearly separates routing and forwarding (i.e., control and transport) [55], therefore a single forwarding mechanism can employ a wide range of routing procedures (with a strong emphasis on constraint-based routing) and routing protocols may base their decisions on multiple metrics, such as bandwidth availability, latency, link costs, etc. [36, Section 5.5.4]. This facilitates the distribution of traffic evenly across the network. 2.8 Generalized Multi-Protocol Label Switching (GM- PLS) RFC 3945 [52] by IETF describes a control plane architecture suitable for hierarchical networks in which several multiplexing layers, e.g., the bundling of optical fibers into cables, Wavelength-Division Multiplexing, subrate multiplexing in wavelengths and many other, upper-layer multiplexing procedures, co-exist simultaneously [45, Section 8.4.3] [59]. It is a generalization of Multi-Protocol Label Switching (MPLS); it is very important to note that the role of GMPLS is not limited to packet forwarding, instead, it assumes control of Packet-Switching Capable, Layer 2 Switching Capable, TDM-Switching Capable, Lambda-Switching Capable and Fiber-Switching Capable devices [36, Section 5.5] [53]. GMPLS propagates inter-operability between layers such as IP and MPLS by defining three inter-operability models, namely, the overlay, the peer and the augmented models. The most important design goals during the conception of GMPLS were (excerpt follows from Alcatel s white paper [53]): 1) Reduction of the number of switching layers, 2) re-use of the label-switching paradigm, 3) re-use of the MPLS-TE protocol suite and mechanisms, and 4) re-use of the IP addressing scheme. As such, GMPLS contributes to bypassing unnecessary layers in an IP/WDM realization by facilitating the interconnection between the IP and WDM layers [66]. For details on the signaling and recovery functions supported by GMPLS, please refer to Bannerjee et al. [67], and Bernstein, Rajagopalan, Saha [36, Chapters 7 and 8]. 25

26 2.8.1 Multi-Region Networks Networks capable of operating multiple switching technologies are referred to as Multi-Region Networks [54]. As described earlier, vertical integration, i.e., co-operation between the control planes of the different technologies is highly desirable. Generalized MPLS supports this requirement by defining collaborative mechanisms between the control planes of the data planes based on different switching technologies. Vertical integration complements horizontal integration, which refers to the facilitation of inter-operation between the control planes of horizontally separated network areas, e.g., different routing areas (autonomous systems) based on a common switching technology. It should be noted that in GMPLS, the term Multi-Layer Network refers to network architectures that employ multiple data plane technologies. A Multi-Region Network is, by definition, also a Multi-Layer Network, but the opposite is not necessarily true Layer Inter-Operability Models for Vertical Integration GMPLS defines three layer inter-operability models, the overlay model, the augmented model and the peer model, which is also known as the unified or integrated model [54] (also note the precursor of this design for interworking between IP and an optical layer [56]). The overlay model (see Figure 2.2(a)) is a legacy model that does not significantly facilitate interworking between the control planes of adjacent layers; it assumes that these layers are operated by different service providers that share a low-trust business relationship. The addressing spaces are separated (translation is required between them) and the exchange of signalling information is strictly limited; the routing and signalling protocols of the control planes act independently of each other and the only way of information exchange between them is through the User-Network Interface (UNI) [47] that defines the client-server relationship between the two layers. This model is opaque and prone to the so-called unknown adjacency problem that results from the duplication of routing functionality [54]: the routing algorithm in the client layer can not determine the adjacencies in the server layer, still, it needs to set up its 26

27 control transport (a) The overlay model (b) The peer model Figure 2.2: Basic Inter-Operability Models own adjacency tables for routing. The server layer can forward information between all possible pairs of nodes, and, as a consequence, the client layer observes a full mesh of adjacencies. This results in complex routing tables (in the client) and drastically impairs scalability. The peer (a.k.a. unified or integrated) model (see Figure 2.2(b)) allows the complete unification of the control planes: it allows a complete exchange of control and signalling information between them while using a common addressing space. Obviously, the algorithmic control of multiple data planes is more complex than that of a single one, but more efficient solutions can achieved this way. The augmented model serves as an intermediate solution between the overlay and peer models. It allows the exchange of a limited (to some extent, customizable) amount of routing information between the client and the server layer, but allows the use of separate addressing spaces. This model provides an adequate compromise for relatively low-trust business models without overly compromising routing efficiency Traffic Engineering Basically, Traffic Engineering [63, 64, 65] is a mechanism for mapping customer data flows onto an existing physical topology [55]. Quoting the Alcatel GMPLS white pa- 27

28 per [53], Traffic Engineering is concerned with network resources and performance optimization, including the application of scientific principles to the measurement, modeling, characterization, and control of traffic, and the application of the corresponding engineering techniques to achieve specific performance objectives. The shortest-path routing with simple, additive link metrics used on the Internet might lead to certain subsets of network resources (mostly those located near the center of the network) becoming congested, while peripheral resources will remain underutilized [63]. Traffic Engineering has the potential of addressing this issue by evening network resource utilization. The application of Traffic Engineering lies in the realization of the routing algorithms. Route selection is possible in two intrinsically different ways: static routing computes all paths in an off-line manner; all actual traffic will be forwarded along the precomputed routes during the operation of the network. Conversely, dynamic or on-line routing computes the best path for individual calls when they arrive in the network; this requires the routing algorithm to be executed for each call. Static routing can only be used when the statistical properties of the traffic (i.e., the traffic matrix) are stable and known in advance; this is mostly true for Erlang-type traffic [32] [33] caused by human interaction, e.g., voice traffic. However, the traffic on networks that also conduct machine-to-machine interaction is neither predictable nor stable, therefore, in this case, static routing leads to bad performance and dynamic routing should be used [64]. This places a computational burden on the network; achieving optimal resource utilization becomes a much more difficult task. Quite obviously, the applicability of Traffic Engineering is not confined to the route computation process during the admission of a call to the network. Calls might be rerouted or terminated after their admission; conversely, blocked calls might be placed in queues waiting for admission and admitted with delay (for a precise definition of calls, please refer to Sections and 4.3). 28

29 2.9 The Automatically Switched Optical Network The Automatically Switched Optical Network is a recommendation proposed by ITU- T [13] [14] [15] [16] [17] comprising a complete control plane reference architecture for automatically switched transport networks [59], that is, transport networks based on SDH [7] and OTN [9]. In the recommendation, three basic connection types are supported: Permanent Connections, which are set up and torn down by the management plane; Soft Permanent Connections, whose user-to-network part is established by the management plane as a Permanent Connection, while the network-network part is maintained as a Switched Connection; and, finally, Switched Connections, which are established on user demand by the signalling/control plane (this involves the dynamic exchange of signalling information between signalling elements of the control plane) [17]. The recommendation describes a control plane whose functionality is threefold: 1) it facilitates the efficient configuration of Switched and Soft Permanent Connections within the transport layer network; 2) provides capability for the reconfiguration of connections that have already been set up; 3) performs a restoration function [16]. The User-Network Interface used by ASON is described in the associated OIF UNI specification [47]. The high-level overview of the ASON architecture is shown on Figure Transport Networks The term transport network refers to the functional resources of any digital telecommunication network which conveys user information between different locations [8]. Very often, transport networks carry highly aggregated signals [1] in order to efficiently use the available resources, like bandwidth, switching devices, processing power, etc (realizing such aggregation remains the task of the control plane). Automatic Switched Transport Network An Automatic Switched Transport Network (ASTN) used to refer to any transport network where configuration connection management is implemented by means of a 29

30 Control Plane CP Management TP Management Resource Management Management Plane TP for management communication Transport Plane TP for signalling DCN (G.7712) Figure 2.3: High-Level Overview of the ASON Architecture control/signalling plane (e.g., ASON [16] or GMPLS [61]) [12, Section 6.2] [17, Section 3.2.5]. As of 2007, the ASTN recommendation has been integrated into ASON. Optical Transport Network The OTN Recommendation [9] is intended to serve as an extension of SONET/SDH [45, Sections 8.4.2]. It provides better error correction, better aggregation capability, reconfigurability, transparent client signal transport, switching scalability, dynamic provisioning and a better support for WDM (interoperability) [19] [45, Section 19.9]. Basically, OTN provides the transport layer for the control and management functions described in ASON Wavelength-Routing Networks Cross-Connect (XC) devices are important building blocks of circuit-switched networks. A typical XC device has as many outputs as inputs, say n (see Figure 2.4(a)); each input may receive a signal, and an arbitrary permutation of the input signals will 30

31 Input ports Output ports n-1 n-1 n n (a) Block diagram of an XC device (b) Possible states (c) Possible states of a 3- of a 2-port XC de- port XC device A D vice C D A F Node 1 Node 2 B F G C E H G Node 3 Node 4 H B E (d) Example: A 4-Node, 2-Wavelength WR Network With 8 Switched Connections: A) 1 2; B) 1 3 4; C) 2 1 3; D) 2 3 1; E) 2 3; F) 3 2; G) 3 4 and H) Figure 2.4: Wavelength-Routing Networks be produced on the respective outputs by switching each input signal exclusively to one output (see Figures 2.4(b) and 2.4(c)). The device can take one of its possible n! states as a response to the control commands received on a dedicated channel. In practice, both electronic and optical cross-connects are available; the latter, abbreviated by OXC, are particularly important in switched optical networks (see Sections 2.8 and 2.9) as core components of network nodes. A Wavelength-Routing (WR) Network [35, Chapter 9] [48, Part III] [73, Section 10.3] provides excellent means of utilizing the capabilities of the WDM technology in gen- 31

32 eral mesh topologies. WR networks consist of Optical Cross-Connect (OXC) [73, Section ] (see also Section 4.1) devices interconnected by optical fiber links and carry the potential of creating transparent (refer to Section and ATIS [1]), switched connections between pairs of network nodes (see also Section 4.1). An example of a 2-wavelength WR network with separate OXCs for each wavelength in the nodes can be seen on Figure 2.4(d). Transparent connections provide a low, fairly constant propagation delay as well as complete independence from, and broad support for, client layer protocols. This independence facilitates co-operation with the client layer as it only needs to coordinate the control functions of the WR network. Present standards allow between one hundred and one thousand wavelengths in a single fiber [2] which subdivide the (at least) 10 THz of available bandwidth. We should note that in the foreseeable future, this amount is unlikely to be fully utilized by the demands of an average end-user. Considering the fact that the bandwidth requirement of a high-quality digital video stream (which we are now considering the most demanding service available to end-users) is typically less than 100 MHz, a scenario where an end-user (meaning one person) requires a bandwidth of more than 100 MHz appears, at least, overly futuristic. It is obvious that optical fibers are well suited for satisfying the combined bandwidth requirements of a large group of end-users (following the bandwidth values cited above, approximately = 10 5 per fiber). Perhaps the most appropriate application of WR networks (and generally, WDM fiber optics) is in the transport planes of core or backbone networks that carry high-density aggregate traffic between subnetworks on lower hierarchical levels of large-scale network architectures Routing and Wavelength Assignment A central issue in the provisioning of WR network resources is the allocation of wavelength channels to lightpaths. Lightpaths provide end-to-end, circuit-switched connections between a pair of physical nodes using a single, previously specified wavelength. First, in order to establish such a connection, one needs to find a reasonably short sequence of physical network links between the endpoints this process is called routing; the resulting sequence will be the assigned route or path of the light- 32

33 path. In a WR network, a set of wavelengths is available on each physical link; lightpaths, on every link belonging to the assigned route, need exactly one of these for exclusive use from setup until termination. Also, a lightpath requires all OXCs traversed along the assigned route to be set to states in which the wavelengths belonging to the lightpath on subsequent links are connected (see Figure 2.4(d) for an example). Conventional OXCs are incapable of wavelength conversion, therefore the wavelength continuity constraint [73, Section ] applies: a lightpath must use the same wavelength on any two consecutive links traversed; clearly, a lightpath must use the same wavelength throughout its whole length. The example on Figure 2.4(d) shows how OXCs may be capable of switching signals upwards, that is, into the client layer of the WR network, where wavelength conversion and even electronic TDM multiplexing may be possible. Whenever a wavelength conversion is needed in a node, the OXC should switch the respective signal to the electronic layer; the electronic layer should return it to the WR network layer unchanged where the OXC may switch it to a different wavelength. Another important constraint is that two lightpaths on the same link must use different wavelengths. Section discusses how this constraint causes bandwidth efficiency issues and introduces traffic grooming, which may partially circumvent this rule. The third constraint is of a different nature: an optical signal gets slightly degraded after traversing a link or a node (see Section 3); it is obvious, that lightpaths can not be arbitrarily long as signal regeneration is not yet possible purely in the optical layer. In large-scale WR networks (trans- or intercontinental backbone networks), signal degradation due to transmission impairments [35, Section 8.2.2] can not be negliged [86] [87] [88]; however, their adverse effects on the performance of routing and wavelength assignment have not been studied extensively. The primary goal of our work is to deal with this necessity. 33

34 Subrate Multiplexing and Traffic Grooming Many types of optical networks face the challenge of efficiently utilizing the bandwidth of optical fibers (see Section 1.4). Wavelength-Division Multiplexing provides a partial solution, but client-layer calls, which correspond to point-to-point, circuitswitched connections of arbitrary bandwidth or transfer rate, usually require various, much smaller magnitudes of bandwidth than the approximately 40 GHz which is available in a WDM wavelength channel. In order to prevent the wasting of bandwidth and allow multiple calls to share the capacity of a wavelength channel, it is desirable to implement an additional level of the GMPLS principle by the means of subrate or subwavelength multiplexing procedures, like TDM or OTDM (see Section 2.5), which allow multiple calls, of possibly different bandwidths, to share a common lightpath. The goal is to group appropriate segments of calls into lightpaths in order to ensure optimal bandwidth usage. Figure 2.5 shows the difference between capacity allocation with and without traffic grooming: in the example, we are trying to allocate the bandwidth of three wavelength channels to five calls of bandwidths (1) 250 GHz, (2) 375 GHz, (3) 125 GHz, (4) 125 GHz and (5) 250 GHz. On Figure 2.5(a), as we are not using traffic grooming, we can only allocate one call per wavelength channel and, therefore, calls 4 and 5 will have to be blocked. Figure 2.5(b) shows the case where traffic grooming allows multiple calls to share the capacity of a single wavelength channel; in this case, all 5 calls can be routed. It is easy to see that while trying to minimize the number of wavelength channels used, accommodating a given set of calls (each requiring a given amount of bandwidth) λ 1 λ 2 λ 3 (a) Without Grooming λ 1 λ 2 λ 3 (b) With Grooming bandwidth (THz) bandwidth (THz) Figure 2.5: The Application of Traffic Grooming in Sharing the Capacity of 3 Wavelength Channels Among a Set of Calls on a single link consisting of a set of channels with uniform capacities is a close analogy of the bin-packing problem [70], which is known to be NP-complete. This problem can be extended to ring and mesh networks as well and other cost functions (e.g., the number of OE/EO conversions) can also be used. Most of these problems have 34

35 proven to be NP-hard and optimal solutions can not be achieved by on-line routing procedures. Very often, the bandwidth of client calls may not be arbitrary. For example, in legacy SDH, the line rate is always an integer multiple of 51, 840 kbps; it is the client s responsibility to ensure the efficient usage of the data rate, which means that above the SDH layer, further multiplexing may be required for accommodating calls whose data rate is below this value. For a transmission system, the largest number G for which it holds that the data rate of a call (with or without overhead) is always a multiple of G, will be referred to as the client data rate granularity of the system. This concept can be applied to a set of calls as well; for example, the set of calls on Figure 2.5 have a granularity of 125 GHz however, we have said nothing about the client data rate granularity of the system. We should note that traffic grooming, in general does not pose any requirements on the client data rates. As a consequence, the client data rate may be very small (depending on the realization), which is a great advantage in efficient bandwidth allocation. We also have to make a distinction between two kinds of problems: static and dynamic grooming (there is a wide range of literature available on the subject [43] [44] [68] [70] [71] [72]). Consider the operation of a network where all connections are provisioned for long periods of time, e.g., months or years; we can always be sure that the set of held calls does not change frequently. Also, when admitting a new call to the network, there may be no stringent requirement that the route be established in a very short period of time: there may even be enough time available for the operator to find the best solution of the NP-hard optimization problem and route all calls accordingly. The important point is that at any time instant, we can predict the set of calls in the network and can optimize the routes accordingly (preferably before establishing any of the calls); this kind of problem is called the static grooming problem. Unfortunately, in automatically provisioned networks, we can not assume the fixed nature of the traffic: calls may occur randomly and there is usually no time to optimize all routes in the network between successive arrivals. In many cases, once a call has been routed, its path can not be altered until termination, since re-routing would require the call traffic to be interrupted (although possibly for a very short interval; many clients, including TCP/IP may tolerate such 35

36 interruptions depending on the frequency). As the set of active calls in the network is continuously changing, this constraint poses a further problem: achieving an optimal route set in the network at any time instant does not imply that achieving an optimal solution later will even be possible without call re-routing. In this case, which is called the dynamic grooming problem, one has to adapt their optimality criteria in accordance with the restricted conditions: given a set of non-reroutable calls already in the network, the goal is to route a set of new calls such that the total number of wavelengths or OE/EO conversions be minimal (one should note that we didn t say anything about when should these measures be minimal). It is often worth assuming that in a very short time interval, at most one traffic demand may arrive; we shall call this kind of traffic strictly dynamic; as the cardinality of the set of new calls is either 0 or 1, an intuitive solution is to use a greedy algorithm (see Section 4.3). For certain special kinds of traffic (e.g., Erlang-type traffic [33, 32]), we are able to predict the statistical properties of arrivals, requested bandwidths and holding times; we can predict the magnitude of traffic to be expected between any pair of network nodes. We can optimize network provisioning accordingly by realizing that certain links are more, some are less prone to being overloaded. Unfortunately, in modern multi-service networks serving large populations, making similar predictions is often difficult. The variety of services and the significance of machine-machine interactions introduce factors that are not easily predictable. Therefore, our approach will assume strictly dynamic traffic. Lightpath tearments Recent work [95] has demonstrated that considerable improvement can be achieved in the performance of dynamic traffic grooming by occasionally allowing a node traversed by a lightpath to tear the lightpath into the electronic layer. Normally, the traffic of a lightpath can not be accessed by intermediate nodes as lightpaths stay exclusively in the optical layer. However, when one wishes to add or drop traffic to or from a lightpath (this is often the case with dynamic grooming), it is necessary to switch the lightpath into the electronic layer, practically by splitting it into two lightpaths. Unfortunately, this results in a short interruption of lightpath traffic (the exact length depends on the type of the switch) hence the name tearment. 36

37 2.11 Next-Generation Networking Next-Generation Networking (NGN) [96] [97] refers to a network architecture capable of providing any digital communication service over a single, IP-based packet switching infrastructure. Such networks require the incorporation of significant network intelligence in order to be able to cater to the requirements of multi-service provisioning. The automatic switching capabilities of DWDM networks supported by GMPLS or ASON control planes provide a solution for facilitating the deployment of IP over WDM (see Section 2.6.2); the resulting architecture provides a convenient base system for NGN service provisionment. 37

38 Chapter 3 Modelling Signal Degradation in the Physical Layer Signals in Wavelength-Routing Networks travel along routes purely in the optical domain that originate at optical signal generators or EO (electronic-to-optical) converters and terminate at optical signal detector or OE (optical-to-electronic) converter devices. Due to the high costs of generators and detectors and the cheapness of optical bandwidth, it is desirable to keep the number of OE and EO conversions to a minimum and forward the signals mostly in the optical domain. Unfortunately, even the best optical devices degrade the quality of such signals in a number of ways. On long fiber segments, the signal loses its power and occasionally needs to be reamplified (e.g., by Erbium-Doped Fiber Amplifiers [51, Section 6.4]) at the cost of incorporating Amplified Spontaneous Emission [73, Section 6.1.1] noise into the signal. The lambda-switching technology employed in WR networks (see Section 2.10) requires signal routes to occasionally traverse OXCs whose complex nature poses further threats to signal quality, mostly in the form of crosstalk. Finally, transmission through the optical fiber in itself also worsens signal quality. It is not unfounded to think that such signal degradations accumulate; that is, the longer the route the signal takes in the optical domain, the higher the amount of signal degradation. If the quality of a signal falls below a certain margin, optical signal detectors might not be able to reproduce the data which was used to modulate the optical light source; in the client layer of the WR network, such events will be perceived as transmission errors. Obviously, network operators are very much interested in accounting for the 38

39 negative effects of such impairments, whose impact, as we will see, depends greatly on the size of the network. Interestingly enough, the effects of transmission impairments on the types of networks discussed herein have not been studied extensively, although, as we will see, significant enhancements could be achieved in terms of performance by taking a few adverse effects into account. Most solutions that have been presented for the RWA problem assume that once a route has been established for a call and the wavelengths used on each link have been identified, the call is feasible. Ramamurthy et al. [86] have developed a model that takes a wide range of physical impairments in a largescale wavelength-routing mesh network into account. They have proven that in a realistic network, blocking probability is significantly higher than in an ideal network free of physical impairments; their approach relies on an on-line model for estimating the expected Bit-Error Rate of each offered call and blocking it if the BER estimate is unacceptably high. The signal quality can vary in time after the admission of a call; however, we assume that once a call has been admitted because of high predicted signal quality, the overall signal degradation will stay in the acceptable range during the holding time of the call. Our work intends to add a slight extension to the approach presented by the article discussed above: as opposed to their one-call-per-wavelength provisioning method, we are incorporating a traffic grooming algorithm into the model. We are also taking Polarization-Mode Dispersion into account; however, with respect to the physical model, we will rely on a slightly different method: instead of direct BER estimation, the so-called Q factor approach will be used [73, Section 6.4]. The model of the physical layer presented in this chapter is an application of the one developed by Zsigmond et al. [87] [88]. 3.1 Phenomena Affecting Optical Signal Quality in Large- Scale WR Networks This work does not seek to give a detailed explanation of the vast range of physical phenomena that might, adversely or conducively, affect the bit error rate of calls; 39

40 many excellent books are available on the subject [51] [73]. We are rather trying to aid the development of a reasonably simple, yet highly practical model which can be used for the on-line evaluation of the signal quality in calls. However, we think it is important to give a brief overview of the effects that are taken into account by our model [87] Polarization-Mode Dispersion (PMD) Signals propagating in an optical fiber are subject to birefringence originating from two sources: geometric or forminduced birefringence and stress-related birefringence. The former is related to small disturbances in the cylindrical symmetry of the cross-section of the fiber, while the latter can be attributed to anisotropic stress produced on the fiber V Δτ H Figure 3.1: Polarization Mode Dispersion along an optical fiber τ is the Differential Group Delay core during the manufacturing and cabling processes [73, Section 3.4]. The latter type might also change with time because of the variations induced on fiber stress by environmental factors (position, temperature, etc.). Birefringence causes the field components polarized along the two principal axes to propagate with different propagation constants: β p is different for the two polarization modes. In realistic fibers, both the magnitude and the orientation of the birefringence vary along the fiber in a random fashion; this causes the state of polarization (SOP) of the signal to change randomly during propagation. Although the final SOP of the signal is of little concern as most detectors are polarization-independent, the random changes in birefringence cause an unpredictable separation (which is sometimes comparable to the bit transmission interval) between the polarization modes at the receiving end of the fiber (see Figure 3.1). When such distortions move pulses outside their respective bit slot, detection errors may occur (see also [51, Section 2.3.5]). 40

41 3.1.2 Amplified Spontaneous Emission (ASE) Erbium-Doped Fiber Amplifiers [51, Section 6.4] are one of the most common type of amplifiers used in DWDM systems (other types with less favorable characteristics include Semiconductor Optical Amplifiers [51, Section 6.2] and Raman Amplifiers [51, Section 6.3]). Their bandwidth is wide enough for multichannel amplification [51, Section 6.4.5]; the ultimate limiting factor for applications is the amplifier noise (Amplified Spontaneous Emission) [51, Section 6.4.4]. The signal amplification effect in EDFAs rely on a large population of excited Er 3+ ions in an Erbium-doped strand of silica fiber; Erbium ions can be excited by pumping with a laser. Amplification occurs when the excited ions return to their base state as a result of stimulation from a modulating signal. However, excited ions may decay randomly in a process known as spontaneous emission; in this case, the ion emits a photon with nearly the same energy as a signal photon, but a random phase. In optical fibers, such spontaneous emissions may occur in all modes of propagation and may interfere with the signal causing noise [73, Section 6.1.1] Crosstalk (XT) Crosstalk in WDM systems can be due to several effects, including the out-of-band linear crosstalk of optical filters [73, Section 9.2.1], in-band linear crosstalk [73, Section 9.2.2], Raman crosstalk [73, Section 9.3.1], Four-Wave Mixing [73, Section 9.3.2] and Cross-Phase Modulation [73, Section 9.4]. The primary effect of these phenomena is that a signal propagating along a specific channel induces a similar signal in a different channel; the induced signal interferes with the original one, causing noise. Accounting individually for each of these sources of crosstalk would most likely lead to an overly complex and cluttered model, hence, we will integrate these effects into a unified way of representation while assuming that crosstalk only occurs in network nodes. 41

42 σ1 I 1 σ 0 I D I 0 Figure 3.2: Calculating the Q Factor from Current Levels. I 1 and I 0 denote the current levels of marks (1) and spaces (0); σ 1 and σ 0 represent the standard deviation of their respective distributions (at sampling), while I D denotes the decision threshold. The red area at the intersection of the two density functions is equal to the bit error probability (in order to demonstrate this correctly, the functions have been distorted). The eye diagram of a 40 Gbps line appearing on the figure is the work of the Institut für Hochfrequenztechnik und Quantenelektronik, Universität Karlsruhe; it has been included with permission from the author (Dr. Jürg Leuthold). 3.2 Calculating the Q Factor Evaluating the Q factor is a simple estimation of the BER of a call [51, Section 4.5.1], [73, Section 6.4]. The relationship between the two measures can be expressed as BER = 1 2 erfc ( Q 2 ) e Q2 /2 Q 2π (3.1) where erfc(x) denotes the complementary error function [98, Section 7.1.2] (the approximate form is obtained using the asymptomatic expansion of erfc(q/ 2) [98, Section ] and is reasonably accurate for Q > 3 [51, Section 4.5.1]); this simple equation gives us a powerful tool for approximating Bit Error Rates of calls. The parameter Q can be obtained using the equation Q = I 1 I 0 σ 1 + σ 0 (3.2) in which I 1 and I 0 denote the mean, σ 1 and σ 0 the standard deviation of mark (1) and space (0) current levels [87, Figure 1] (see Figure 3.2). 42