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

A constrained maximum available frequency slots on path based online routing and spectrum allocation for dynamic traffic in elastic optical networks

Elastic optical networking is a potential candidate to support dynamic traffic with heterogeneous data rates and variable bandwidth requirements with the support of the optical orthogonal frequency division multiplexing technology (OOFDM). During the dynamic network operation, lightpath arrives and departs frequently and the network status updates accordingly. Fixed routing and alternate routing algorithms do not tune according to the current network status which are computed offline. Therefore, offline algorithms greedily use resources with an objective to compute shortest possible paths and results in high blocking probability during dynamic network operation. In this paper, adaptive routing algorithms are proposed for shortest path routing as well as alternate path routing which make routing decision based on the maximum idle frequency slots (FS) available on different paths. The proposed algorithms select an underutilized path between different choices with maximum idle FS and efficiently avoids utilizing a congested path. The proposed routing algorithms are compared with offline routing algorithms as well as an existing adaptive routing algorithm in different network scenarios. It has been shown that the proposed algorithms efficiently improve network performance in terms of FS utilization and blocking probability during dynamic network operation

Routing, Modulation and Spectrum Assignment Algorithm Using Multi-Path Routing and Best-Fit

Producción CientíficaElastic Optical Networks (EONs) are a promising optical technology to deal with the ever-increasing traffic and the vast number of connected devices of the next generation of the Internet, associated to paradigms like the Internet of Things (IoT), the Tactile Internet or the Industry 4.0, to name just a few. In this kind of optical network, each optical circuit or lightpath is provisioned by means of superchannels of variable bandwidth. In this manner, only the necessary bandwidth to accommodate the demand is allocated, improving the spectrum usage. When establishing a connection, the EON control layer determines the modulation format to be used and allocates a portion of the spectrum in a sequence of fibers from the source to the destination node providing the user-demanded bandwidth. This is known as the routing, modulation level and spectrum assignment (RMSA) problem. In this work, we firstly review the most important contributions in that area, and then, we propose a novel RMSA algorithm, multi-path best-fit (MP-BF), which uses a split spectrum multi-path strategy together with a spectrum assignment technique (best-fit), and which jointly exploit the flexibility of EONs. A simulation study has been conducted comparing the performance of EONs when using MP-BF with other proposals from the literature. The results of this study show that, by using MP-BF, the network can increase its performance in terms of lightpath request blocking ratio and supported traffic load, without affecting the energy per bit or the computation time required to find a solution

Spectrum Allocation Suppressing Fragmentation Proactively in Elastic Optical Networks

エラスティック光ネットワーク(EON: Elastic Optical Network) において，帯域フラグメンテーションは，サブキャリアスロットのセットにおける未使用である未整列・非連続のサブキャリアの存在によって生じる。コネクションが使用する波長は，連続したサブキャリアスロットに割り当てられなければならないので，これらの未整列・非連続サブキャリアスロットは，帯域ブロッキングの原因となる。本論文はエラスティック光ネットワークにおけるスペクトル分断を抑制するスペクトル割り当てを提案する。２つ方式、サブキャリアスロット分割方式とfirst-last-exact fit 割り当てポリシー、が提示された。１つ目の方式には、1 つの同一のリンクを共有していないコネクションは同じパティションに割り当てられて、同一のリンクを使用するコネクションは別のパティションに割り当てられた。こうしてより多くの整列サブキャリアスロットを生成し。また、奇数インデックスのパティションはfirst fit波長割り当てポリシーを採用して、偶数インデックスのパティションはlast-fit波長割り当てポリシーを採用した。こうしてより多くの連続したサブキャリアスロットを生成し。２つ目の方式には、1 つの同一のリンクを共有していないコネクションはfirst-exact fit波長割り当てポリシーを採用して、同一のリンクを使用するコネクションはlast-exact fit波長割り当てポリシーを採用した。こうしてもより多くの整列・連続したサブキャリアスロットを生成し。提案方式は，より多くの整列・連続したサブキャリアスロットを生成し，帯域ブロッキングを削減する。シミュレーション結果により従来方式と比べ，帯域ブロッキングを削減することが定量的に示されている。電気通信大学201

Priority realloc : a threefold mechanism for route and resources allocation in EONs

Cotutela Universitat Politècnica de Catalunya i Escola Politécnica da Universidade de São PauloBackbone networks are responsible for long-haul data transport serving many clients with a large volume of data. Since long-haul data transport service must rely on a robust high capacity network the current technology broadly adopted by the industry is Wavelength Division Multiplexing (WDM). WDM networks enable one single fiber to operate with multiple high capacity channels, drastically increasing the fiber capacity. In WDM networks each channel is associated with an individual wavelength. Therefore a whole wavelength capacity is assigned to a connection, causing waste of bandwidth in case the connection bandwidth requirement is less than the channel total capacity. In the last half decade, Elastic Optical Networks (EON) have been proposed and developed based on the flexible use of the optical spectrum known as the flexigrid. EONs are adaptable to clients requirements and may enhance optical networks performance. For these reasons, research community and data transport providers have been demonstrating increasingly high interest in EONs which are likely to replace WDM as the universally adopted technology in backbone networks in the near future. EONs have two characteristics that may limit its efficient resources use. The spectrum fragmentation, inherent to the dynamic EON operation, decreases the network capacity to assign resources to connection requests increasing network blocking probability. The spectrum fragmentation also intensifies the denial of service to higher rate request inducing service unfairness. Due to the fact EONs were just recently developed and proposed, the aforementioned issues were not yet extensively studied and solutions are still being proposed. Furthermore, EONs do not yet provide specific features as differentiated service mechanisms. Differentiated service strategies are important in backbone networks to guarantee client's diverse requirements in case of a network failure or the natural congestion and resources contention that may occur at some periods of time in a network. Impelled by the foregoing facts, this thesis objective is three-fold. By means of developing and proposing a mechanism for routing and resources assignment in EONs, we intend to provide differentiated service while decreasing fragmentation level and increasing service fairness. The mechanism proposed and explained in this thesis was tested in an EON simulation environment and performance results indicated that it promotes beneficial performance enhancements when compared to benchmark algorithms.Redes backbone sao responsáveis pelo transporte de dados à longa distância que atendem a uma grande quantidade de clientes com um grande volume de dados. Como redes backbone devem basear-se em uma rede robusta e de alta capacidade, a tecnologia atual amplamente adotada pela indústria é Wavelength Division Multiplexing (WDM). Redes WDM permitem que uma única fibra opere com múltiplos canais de alta largura de banda, aumentando drasticamente a capacidade da fibra. Em redes WDM cada canal está associado a um comprimento de onda particular. Por conseguinte, toda capacidade do comprimento de onda é atribuída a uma única conexão, fazendo com que parte da largura de banda seja desperdiçada no caso em que a requisição de largura de banda da conexão seja menor do que a capacidade total do canal. A partir da metade da última década, as Redes Ópticas Elásticas (Elastic Optical Networks - EON) têm sido propostas e desenvolvidas com base no uso flexível do espectro óptico conhecido como flexigrid. EONs são adaptáveis às requisiçes por banda dos clientes e podem, portanto, melhorar o desempenho das redes ópticas. Por estas razões, EONs têm recebido cada vez mais interesse dos meios de pesquisa e provedores de serviço e provavelmente substituirão WDM como a tecnologia universalmente adotada pela indústria em redes backbone. EONs têm duas características que podem limitar a utilização eficiente de recursos. A fragmentação do espectro, inerente à operação dinâmica das EONs, pode diminuir a capacidade da rede em distribuir recursos ao atender às solicitações por conexões aumentando a probabilidade de bloqueio na rede. A fragmentação do espectro também intensifica a negação de serviço às solicitações por taxa de transmissão mais elevada, gerando injustiça no serviço prestado. Como EONs foram desenvolvidas recentemente, respostas às questões acima mencionadas ainda estão sob estudo e soluções continuam sendo propostas na literatura. Além disso, EONs ainda não fornecem funções específicas como um mecanismo que proveja diferenciação de serviço. Estratégias de diferenciação de serviço são importantes em redes backbone para garantir os diversos requisitos dos clientes em caso de uma falha na rede ou do congestionamento e disputa por recursos que podem ocorrer em alguns períodos em uma rede. Impulsionada pelos fatos anteriormente mencionados, esta tese possui três objetivos. Através do desenvolvimento e proposta de um mecanismo de roteamento e atribuição de recursos para EONs, temos a intenção de disponibilizar diferenciação de serviço, diminuir o nível de fragmentação de espectro e aumentar a justiça na distribuição de serviços. O mecanismo proposto nesta tese foi testado em simulações de EONs. Resultados indicaram que o mecanismo proposto promove benefícios através do aprimoramento da performance de uma rede EON quando comparado com algoritmos de referência.Les xarxes troncals son responsables per el transport de dades a llarga distància que serveixen a una gran quantitat de clients amb un gran volum de dades. Com les xarxes troncals han d'estar basades en una xarxa robusta i d'alta capacitat, la tecnologia actual àmpliament adoptada per la indústria és el Wavelength Division Multiplexing (WDM). Xarxes WDM permeten operar amb una sola fibra multicanal d'alt ample de banda, el que augmenta molt la capacitat de la fibra. A les xarxes WDM cada canal est a associat amb una longitud d'ona particular. En conseqüència, tota la capacitat del canal es assignada a una sola connexió, fent que part dels recurs siguin perduts en el cas en que l'ample de banda sol licitada sigui menys que la capacitat total del canal. A gairebé deu anys les xarxes òptiques elàstiques (Elastic Optical Networks -EON) son propostes i desenvolupades basades en el ús visible de l'espectre òptic conegut com Flexigrid. EONs són adaptables a les sol·licituds per ample de banda dels clients i per tant poden millorar el rendiment de les xarxes òptiques. Per aquestes raons, EONs han rebut cada vegada més interès en els mitjans d’investigació i de serveis i, probablement, han de reemplaçar el WDM com la tecnologia universalment adoptada en les xarxes troncals. EONs tenen dues característiques que poden limitar l'ús eficient dels recursos seus. La fragmentació de l'espectre inherent al funcionament dinàmic de les EONs, pot disminuir la capacitat de la xarxa en distribuir els recursos augmentant la probabilitat de bloqueig de connexions. La fragmentació de l'espectre també intensifica la denegació de les sol·licituds de servei per connexions amb una major ample de banda, el que genera injustícia en el servei ofert. Com les EONs s'han desenvolupat recentment, solucions als problemes anteriors encara estan en estudi i les solucions segueixen sent proposades en la literatura. D'altra banda, les EONs encara no proporcionen funcions especifiques com mecanisme de diferenciació de provisió de serveis. Estratègies de diferenciació de servei són importants en les xarxes troncals per garantir les diverses necessitats dels clients en cas d'una fallada de la xarxa o de la congestió i la competència pels recursos que es poden produir en alguns períodes. Impulsada pels fets abans esmentats, aquesta tesi te tres objectius. A través del desenvolupament i proposta d'un mecanisme d'enrutament i assignació de recursos per EONs, tenim la intenció d'oferir la diferenciació de serveis, disminuir el nivell de fragmentació de l'espectre i augmentar l'equitat en la distribució dels serveis. El mecanisme proposat en aquesta tesi ha estat provat en simulacions EONs. Els resultats van indicar que el mecanisme promou millores en el rendiment de la EON, en comparació amb els algoritmes de referència.Postprint (published version

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

Class-based first-fit spectrum allocation with fragmentation avoidance for dynamic flexgrid optical networks

Cataloged from PDF version of article.A novel Class-Based First Fit (CBFF) spectrum allocation policy is proposed for dynamic flexgrid optical networks. The effectiveness of the proposed CBFF policy is compared with that of the First Fit (FF) policy for single-link and network scenarios. Throughput is shown to be consistently improved under the proposed CBFF policy with throughput gains of up to 15%, compared with the FF policy for the network scenarios we studied. The reduction in bandwidth blocking probability with CBFF with respect to FF increases as the link capacities increase. Throughput gains of CBFF compared with those of FF are more significant under alternate routing as opposed to fixed routing. © 2014 Elsevier B.V. All rights reserved

An Overview on Application of Machine Learning Techniques in Optical Networks

Today's telecommunication networks have become sources of enormous amounts of widely heterogeneous data. This information can be retrieved from network traffic traces, network alarms, signal quality indicators, users' behavioral data, etc. Advanced mathematical tools are required to extract meaningful information from these data and take decisions pertaining to the proper functioning of the networks from the network-generated data. Among these mathematical tools, Machine Learning (ML) is regarded as one of the most promising methodological approaches to perform network-data analysis and enable automated network self-configuration and fault management. The adoption of ML techniques in the field of optical communication networks is motivated by the unprecedented growth of network complexity faced by optical networks in the last few years. Such complexity increase is due to the introduction of a huge number of adjustable and interdependent system parameters (e.g., routing configurations, modulation format, symbol rate, coding schemes, etc.) that are enabled by the usage of coherent transmission/reception technologies, advanced digital signal processing and compensation of nonlinear effects in optical fiber propagation. In this paper we provide an overview of the application of ML to optical communications and networking. We classify and survey relevant literature dealing with the topic, and we also provide an introductory tutorial on ML for researchers and practitioners interested in this field. Although a good number of research papers have recently appeared, the application of ML to optical networks is still in its infancy: to stimulate further work in this area, we conclude the paper proposing new possible research directions