Management of Spectral Resources in Elastic Optical Networks

Recent developments in the area of mobile technologies, data center networks, cloud computing and social networks have triggered the growth of a wide range of network applications. The data rate of these applications also vary from a few megabits per second (Mbps) to several Gigabits per second (Gbps), thereby increasing the burden on the Inter- net. To support this growth in Internet data traffic, one foremost solution is to utilize the advancements in optical networks. With technology such as wavelength division multiplexing (WDM) networks, bandwidth upto 100 Gbps can be exploited from the optical fiber in an energy efficient manner. However, WDM networks are not efficient when the traffic demands vary frequently. Elastic Optical Networks (EONs) or Spectrum Sliced Elastic Optical Path Networks (SLICE) or Flex-Grid has been recently proposed as a long-term solution to handle the ever-increasing data traffic and the diverse demand range. EONs provide abundant bandwidth by managing the spectrum resources as fine-granular orthogonal sub-carriers that makes it suitable to accommodate varying traffic demands. However, the Routing and Spectrum Allocation (RSA) algorithm in EONs has to follow additional constraints while allocating sub-carriers to demands. These constraints increase the complexity of RSA in EONs and also, make EONs prone to the fragmentation of spectral resources, thereby decreasing the spectral efficiency. The major objective of this dissertation is to study the problem of spectrum allocation in EONs under various network conditions. With this objective, this dissertation presents the author\u27s study and research on multiple aspects of spectrum allocation in EONs: how to allocate sub-carriers to the traffic demands, how to accommodate traffic demands that varies with time, how to minimize the fragmentation of spectral resources and how to efficiently integrate the predictability of user demands for spectrum assignment. Another important contribution of this dissertation is the application of EONs as one of the substrate technologies for network virtualization

Stochastische Analyse und lernbasierte Algorithmen zur Ressourcenbereitstellung in optischen Netzwerken

The unprecedented growth in Internet traffic has driven the innovations in provisioning of optical resources as per the need of bandwidth demands such that the resource utilization and spectrum efficiency could be maximized. With the advent of the next generation flexible optical transponders and switches, the flexible-grid-based elastic optical network (EON) is foreseen as an alternative to the widely deployed fixed-grid-based wavelength division multiplexing networks. At the same time, the flexible resource provisioning also raises new challenges for EONs. One such challenge is the spectrum fragmentation. As network traffic varies over time, spectrum gets fragmented due to the setting up and tearing down of non-uniform bandwidth requests over aligned (i.e., continuous) and adjacent (i.e., contiguous) spectrum slices, which leads to a non-optimal spectrum allocation, and generally results in higher blocking probability and lower spectrum utilization in EONs. To address this issue, the allocation and reallocation of optical resources are required to be modeled accurately, and managed efficiently and intelligently. The modeling of routing and spectrum allocation in EONs with the spectrum contiguity and spectrum continuity constraints is well-investigated, but existing models do not consider the fragmentation issue resulted by these constraints and non-uniform bandwidth demands. This thesis addresses this issue and considers both the constraints to computing exact blocking probabilities in EONs with and without spectrum conversion, and with spectrum reallocation (known as defragmentation) for the first time using the Markovian approach. As the exact network models are not scalable with respect to the network size and capacity, this thesis proposes load-independent and load-dependent approximate models to compute approximate blocking probabilities in EONs. Results show that the connection blocking due to fragmentation can be reduced by using a spectrum conversion or a defragmentation approach, but it can not be eliminated in a mesh network topology. This thesis also deals with the important network resource provisioning task in EONs. To this end, it first presents algorithmic solutions to efficiently allocate and reallocate spectrum resources using the fragmentation factor along spectral, time, and spatial dimensions. Furthermore, this thesis highlights the role of machine learning techniques in alleviating issues in static provisioning of optical resources, and presents two use-cases: handling time-varying traffic in optical data center networks, and reducing energy consumption and allocating spectrum proportionately to traffic classes in fiber-wireless networks.Die flexible Nutzung des Spektrums bringt in Elastischen Optischen Netze (EON) neue Herausforderungen mit sich, z.B., die Fragmentierung des Spektrums. Die Fragmentierung entsteht dadurch, dass die Netzwerkverkehrslast sich im Laufe der Zeit ändert und so wird das Spektrum aufgrund des Verbindungsaufbaus und -abbaus fragmentiert. Das für eine Verbindung notwendige Spektrum wird durch aufeinander folgende (kontinuierliche) und benachbarte (zusammenhängende) Spektrumsabschnitte (Slots) gebildet. Dies führt nach den zahlreichen Reservierungen und Freisetzungen des Spektrums zu einer nicht optimalen Zuordnung, die in einer höheren Blockierungs-wahrscheinlichkeit der neuen Verbindungsanfragen und einer geringeren Auslastung von EONs resultiert. Um dieses Problem zu lösen, müssen die Zuweisung und Neuzuordnung des Spektrums in EONs genau modelliert und effizient sowie intelligent verwaltet werden. Diese Arbeit beschäftigt sich mit dem Fragmentierungsproblem und berücksichtigt dabei die beiden Einschränkungen: Kontiguität und Kontinuität. Unter diesen Annahmen wurden analytische Modelle zur Berechnung einer exakten Blockierungswahrscheinlichkeit in EONs mit und ohne Spektrumskonvertierung erarbeitet. Außerdem umfasst diese Arbeit eine Analyse der Blockierungswahrscheinlichkeit im Falle einer Neuzuordnung des Sprektrums (Defragmentierung). Diese Blockierungsanalyse wird zum ersten Mal mit Hilfe der Markov-Modelle durchgeführt. Da die exakten analytischen Modelle hinsichtlich der Netzwerkgröße und -kapazität nicht skalierbar sind, werden in dieser Dissertation verkehrslastunabhängige und verkehrslastabhängige Approximationsmodelle vorgestellt. Diese Modelle bieten eine Näherung der Blockierungswahrscheinlichkeiten in EONs. Die Ergebnisse zeigen, dass die Blockierungswahrscheinlichkeit einer Verbindung aufgrund von einer Fragmentierung des Spektrums durch die Verwendung einer Spektrumkonvertierung oder eines Defragmentierungsverfahrens verringert werden kann. Eine effiziente Bereitstellung der optischen Netzwerkressourcen ist eine wichtige Aufgabe von EONs. Deswegen befasst sich diese Arbeit mit algorithmischen Lösungen, die Spektrumressource mithilfe des Fragmentierungsfaktors von Spektral-, Zeit- und räumlichen Dimension effizient zuweisen und neu zuordnen. Darüber hinaus wird die Rolle des maschinellen Lernens (ML) für eine verbesserte Bereitstellung der optischen Ressourcen untersucht und das ML basierte Verfahren mit der statischen Ressourcenzuweisung verglichen. Dabei werden zwei Anwendungsbeispiele vorgestellt und analysiert: der Umgang mit einer zeitveränderlichen Verkehrslast in optischen Rechenzentrumsnetzen, und eine Verringerung des Energieverbrauchs und die Zuweisung des Spektrums proportional zu Verkehrsklassen in kombinierten Glasfaser-Funknetzwerken

Optical Networks and Interconnects

The rapid evolution of communication technologies such as 5G and beyond, rely on optical networks to support the challenging and ambitious requirements that include both capacity and reliability. This chapter begins by giving an overview of the evolution of optical access networks, focusing on Passive Optical Networks (PONs). The development of the different PON standards and requirements aiming at longer reach, higher client count and delivered bandwidth are presented. PON virtualization is also introduced as the flexibility enabler. Triggered by the increase of bandwidth supported by access and aggregation network segments, core networks have also evolved, as presented in the second part of the chapter. Scaling the physical infrastructure requires high investment and hence, operators are considering alternatives to optimize the use of the existing capacity. This chapter introduces different planning problems such as Routing and Spectrum Assignment problems, placement problems for regenerators and wavelength converters, and how to offer resilience to different failures. An overview of control and management is also provided. Moreover, motivated by the increasing importance of data storage and data processing, this chapter also addresses different aspects of optical data center interconnects. Data centers have become critical infrastructure to operate any service. They are also forced to take advantage of optical technology in order to keep up with the growing capacity demand and power consumption. This chapter gives an overview of different optical data center network architectures as well as some expected directions to improve the resource utilization and increase the network capacity

Machine learning for optical fiber communication systems: An introduction and overview

Optical networks generate a vast amount of diagnostic, control and performance monitoring data. When information is extracted from this data, reconfigurable network elements and reconfigurable transceivers allow the network to adapt both to changes in the physical infrastructure but also changing traffic conditions. Machine learning is emerging as a disruptive technology for extracting useful information from this raw data to enable enhanced planning, monitoring and dynamic control. We provide a survey of the recent literature and highlight numerous promising avenues for machine learning applied to optical networks, including explainable machine learning, digital twins and approaches in which we embed our knowledge into the machine learning such as physics-informed machine learning for the physical layer and graph-based machine learning for the networking layer

In-operation planning in flexgrid optical core networks

New generation applications, such as cloud computing or video distribution, can run in a telecom cloud infrastructure where the datacenters (DCs) of telecom operators are integrated in their networks thus, increasing connections' dynamicity and resulting in time-varying traffic capacities, which might also entail changes in the traffic direction along the day. As a result, a flexible optical technology able to dynamically set-up variable-capacity connections, such as flexgrid, is needed. Nonetheless, network dynamicity might entail network performance degradation thus, requiring re-optimizing the network while it is in operation. This thesis is devoted to devise new algorithms to solve in-operation network planning problems aiming at enhancing the performance of optical networks and at studying their feasibility in experimental environments. In-operation network planning requires from an architecture enabling the deployment of algorithms that must be solved in stringent times. That architecture can be based on a Path Computation Element (PCE) or a Software Defined Networks controller. In this thesis, we assume the former split in a front-end PCE, in charge of provisioning paths and handling network events, and a specialized planning tool in the form of a back-end PCE responsible for solving in-operation planning problems. After the architecture to support in-operation planning is assessed, we focus on studying the following applications: 1) Spectrum fragmentation is one of the most important problems in optical networks. To alleviate it to some extent without traffic disruption, we propose a hitless spectrum defragmentation strategy. 2) Each connection affected by a failure can be recovered using multiple paths to increase traffic restorability at the cost of poor resource utilization. We propose re-optimizing the network after repairing the failure to aggregate and reroute those connections to release spectral resources. 3) We study two approaches to provide multicast services: establishing a point-to-multipoint connections at the optical layer and using multi-purpose virtual network topologies (VNT) to serve both unicast and multicast connectivity requests. 4) The telecom cloud infrastructure, enables placing contents closer to the users. Based on it, we propose a hierarchical content distribution architecture where VNTs permanently interconnect core DCs and metro DCs periodically synchronize contents to the core DCs. 5) When the capacity of the optical backbone network becomes exhausted, we propose using a planning tool with access to inventory and operation databases to periodically decide the equipment and connectivity to be installed at the minimum cost reducing capacity overprovisioning. 6) In multi-domain multi-operator scenarios, a broker on top of the optical domains can provision multi-domain connections. We propose performing intra-domain spectrum defragmentation when no contiguous spectrum can be found for a new connection request. 7) Packet nodes belonging to a VNT can collect and send incoming traffic monitoring data to a big data repository. We propose using the collected data to predict next period traffic and to adapt the VNT to future conditions. The methodology followed in this thesis consists in proposing a problem statement and/or a mathematical formulation for the problems identified and then, devising algorithms for solving them. Those algorithms are simulated and then, they are experimentally assessed in real test-beds. This thesis demonstrates the feasibility of performing in-operation planning in optical networks, shows that it enhances the performance of the network and validates the feasibility of its deployment in real networks. It shall be mentioned that part of the work reported in this thesis has been done within the framework of several research projects, namely IDEALIST (FP7-ICT-2011-8) and GEANT (238875) funded by the EC and SYNERGY (TEC2014-59995-R) funded by the MINECO.Les aplicacions de nova generació, com ara el cloud computing o la distribució de vídeo, es poden executar a infraestructures de telecom cloud (TCI) on operadors integren els seus datacenters (DC) a les seves xarxes. Aquestes aplicacions fan que incrementi tant la dinamicitat de les connexions, com la variabilitat de les seves capacitats en el temps, arribant a canviar de direcció al llarg del dia. Llavors, cal disposar de tecnologies òptiques flexibles, tals com flexgrid, que suportin aquesta dinamicitat a les connexions. Aquesta dinamicitat pot degradar el rendiment de la xarxa, obligant a re-optimitzar-la mentre és en operació. Aquesta tesis està dedicada a idear nous algorismes per a resoldre problemes de planificació sobre xarxes en operació (in-operation network planning) per millorar el rendiment de les xarxes òptiques i a estudiar la seva factibilitat en entorns experimentals. Aquests problemes requereixen d’una arquitectura que permeti desplegar algorismes que donin solucions en temps restrictius. L’arquitectura pot estar basada en un Element de Computació de Rutes (PCE) o en un controlador de Xarxes Definides per Software. En aquesta tesis, assumim un PCE principal encarregat d’aprovisionar rutes i gestionar esdeveniments de la xarxa, i una eina de planificació especialitzada en forma de PCE de suport per resoldre problemes d’in-operation planning. Un cop validada l’arquitectura que dona suport a in-operation planning, estudiarem les següents aplicacions: 1) La fragmentació d’espectre és un dels principals problemes a les xarxes òptiques. Proposem reduir-la en certa mesura, fent servir una estratègia que no afecta al tràfic durant la desfragmentació. 2) Cada connexió afectada per una fallada pot ser recuperada fent servir múltiples rutes incrementant la restaurabilitat de la xarxa, tot i empitjorar-ne la utilització de recursos. Proposem re-optimitzar la xarxa després de reparar una fallada per agregar i re-enrutar aquestes connexions tractant d’alliberar recursos espectrals. 3) Estudiem dues solucions per aprovisionar serveis multicast: establir connexions punt-a-multipunt sobre la xarxa òptica i utilitzar Virtual Network Topologies (VNT) multi-propòsit per a servir peticions de connectivitat tant unicast com multicast. 4) La TCI permet mantenir els continguts a prop dels usuaris. Proposem una arquitectura jeràrquica de distribució de continguts basada en la TCI, on els DC principals s’interconnecten per mitjà de VNTs permanents i els DCs metropolitans periòdicament sincronitzen continguts amb els principals. 5) Quan la capacitat de la xarxa òptica s’exhaureix, proposem utilitzar una eina de planificació amb accés a bases de dades d’inventari i operacionals per decidir periòdicament l’equipament i connectivitats a instal·lar al mínim cost i reduir el sobre-aprovisionament de capacitat. 6) En entorns multi-domini multi-operador, un broker per sobre dels dominis òptics pot aprovisionar connexions multi-domini. Proposem aplicar desfragmentació d’espectre intra-domini quan no es pot trobar espectre contigu per a noves peticions de connexió. 7) Els nodes d’una VNT poden recollir i enviar informació de monitorització de tràfic entrant a un repositori de big data. Proposem utilitzar aquesta informació per adaptar la VNT per a futures condicions. La metodologia que hem seguit en aquesta tesis consisteix en formalitzar matemàticament els problemes un cop aquests son identificats i, després, idear algorismes per a resoldre’ls. Aquests algorismes son simulats i finalment validats experimentalment en entorns reals. Aquesta tesis demostra la factibilitat d’implementar mecanismes d’in-operation planning en xarxes òptiques, mostra els beneficis que aquests aporten i valida la seva aplicabilitat en xarxes reals. Part del treball presentat en aquesta tesis ha estat dut a terme en el marc dels projectes de recerca IDEALIST (FP7-ICT-2011-8) i GEANT (238875), finançats per la CE, i SYNERGY (TEC2014-59995-R), finançat per el MINECO.Postprint (published version

Robust regenerator allocation in nonlinear flexible-grid optical networks with time-varying data rates

Predeployment of regenerators in a selected subset of network nodes allows service providers to achieve rapid provisioning of traffic demands, high utilization, and reduced network operational costs, while still guaranteeing lightpath quality of transmission. Enabled by bandwidth-variable transceivers in flexible-grid optical networks, optical channel bandwidths are no longer fixed but constantly changing according to real-time communication requirements. Consequently, the data-rate-variable traffic together with other new network features introduced by flexible-grid networks will render the regenerator allocation very difficult due to the complicated network states. In this paper, we investigate how to allocate regenerators robustly in flexible-grid optical networks to combat physical-layer impairments when the data rates of traffic demands are random variables. The Gaussian noise model and a modified statistical network assessment process framework are used to characterize the probabilistic distributions of physical-layer impairments for each demand, based on which a heuristic algorithm is proposed to select a set of regenerator sites with minimum blocking probabilities. Our method achieves the same blocking probabilities with on average 10% less regenerator sites compared with the greedy constrained-routing regenerator allocation method, and obtains blocking probabilities two orders of magnitude lower than that of the routing and reach method with the same number of regenerator sites

Enabling Technology in Optical Fiber Communications: From Device, System to Networking

This book explores the enabling technology in optical fiber communications. It focuses on the state-of-the-art advances from fundamental theories, devices, and subsystems to networking applications as well as future perspectives of optical fiber communications. The topics cover include integrated photonics, fiber optics, fiber and free-space optical communications, and optical networking

Virtualisation and resource allocation in MECEnabled metro optical networks

The appearance of new network services and the ever-increasing network traffic and number of connected devices will push the evolution of current communication networks towards the Future Internet. In the area of optical networks, wavelength routed optical networks (WRONs) are evolving to elastic optical networks (EONs) in which, thanks to the use of OFDM or Nyquist WDM, it is possible to create super-channels with custom-size bandwidth. The basic element in these networks is the lightpath, i.e., all-optical circuits between two network nodes. The establishment of lightpaths requires the selection of the route that they will follow and the portion of the spectrum to be used in order to carry the requested traffic from the source to the destination node. That problem is known as the routing and spectrum assignment (RSA) problem, and new algorithms must be proposed to address this design problem. Some early studies on elastic optical networks studied gridless scenarios, in which a slice of spectrum of variable size is assigned to a request. However, the most common approach to the spectrum allocation is to divide the spectrum into slots of fixed width and allocate multiple, consecutive spectrum slots to each lightpath, depending on the requested bandwidth. Moreover, EONs also allow the proposal of more flexible routing and spectrum assignment techniques, like the split-spectrum approach in which the request is divided into multiple "sub-lightpaths". In this thesis, four RSA algorithms are proposed combining two different levels of flexibility with the well-known k-shortest paths and first fit heuristics. After comparing the performance of those methods, a novel spectrum assignment technique, Best Gap, is proposed to overcome the inefficiencies emerged when combining the first fit heuristic with highly flexible networks. A simulation study is presented to demonstrate that, thanks to the use of Best Gap, EONs can exploit the network flexibility and reduce the blocking ratio. On the other hand, operators must face profound architectural changes to increase the adaptability and flexibility of networks and ease their management. Thanks to the use of network function virtualisation (NFV), the necessary network functions that must be applied to offer a service can be deployed as virtual appliances hosted by commodity servers, which can be located in data centres, network nodes or even end-user premises. The appearance of new computation and networking paradigms, like multi-access edge computing (MEC), may facilitate the adaptation of communication networks to the new demands. Furthermore, the use of MEC technology will enable the possibility of installing those virtual network functions (VNFs) not only at data centres (DCs) and central offices (COs), traditional hosts of VFNs, but also at the edge nodes of the network. Since data processing is performed closer to the enduser, the latency associated to each service connection request can be reduced. MEC nodes will be usually connected between them and with the DCs and COs by optical networks. In such a scenario, deploying a network service requires completing two phases: the VNF-placement, i.e., deciding the number and location of VNFs, and the VNF-chaining, i.e., connecting the VNFs that the traffic associated to a service must transverse in order to establish the connection. In the chaining process, not only the existence of VNFs with available processing capacity, but the availability of network resources must be taken into account to avoid the rejection of the connection request. Taking into consideration that the backhaul of this scenario will be usually based on WRONs or EONs, it is necessary to design the virtual topology (i.e., the set of lightpaths established in the networks) in order to transport the tra c from one node to another. The process of designing the virtual topology includes deciding the number of connections or lightpaths, allocating them a route and spectral resources, and finally grooming the traffic into the created lightpaths. Lastly, a failure in the equipment of a node in an NFV environment can cause the disruption of the SCs traversing the node. This can cause the loss of huge amounts of data and affect thousands of end-users. In consequence, it is key to provide the network with faultmanagement techniques able to guarantee the resilience of the established connections when a node fails. For the mentioned reasons, it is necessary to design orchestration algorithms which solve the VNF-placement, chaining and network resource allocation problems in 5G networks with optical backhaul. Moreover, some versions of those algorithms must also implements protection techniques to guarantee the resilience system in case of failure. This thesis makes contribution in that line. Firstly, a genetic algorithm is proposed to solve the VNF-placement and VNF-chaining problems in a 5G network with optical backhaul based on star topology: GASM (genetic algorithm for effective service mapping). Then, we propose a modification of that algorithm in order to be applied to dynamic scenarios in which the reconfiguration of the planning is allowed. Furthermore, we enhanced the modified algorithm to include a learning step, with the objective of improving the performance of the algorithm. In this thesis, we also propose an algorithm to solve not only the VNF-placement and VNF-chaining problems but also the design of the virtual topology, considering that a WRON is deployed as the backhaul network connecting MEC nodes and CO. Moreover, a version including individual VNF protection against node failure has been also proposed and the effect of using shared/dedicated and end-to-end SC/individual VNF protection schemes are also analysed. Finally, a new algorithm that solves the VNF-placement and chaining problems and the virtual topology design implementing a new chaining technique is also proposed. Its corresponding versions implementing individual VNF protection are also presented. Furthermore, since the method works with any type of WDM mesh topologies, a technoeconomic study is presented to compare the effect of using different network topologies in both the network performance and cost.Departamento de Teoría de la Señal y Comunicaciones e Ingeniería TelemáticaDoctorado en Tecnologías de la Información y las Telecomunicacione