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

Contributions to network planning and operation of Flex-Grid/SDM optical core networks

Premi Extraordinari de Doctorat, promoció 2018-2019. Àmbit de les TICThe ever demanding bandwidth requirements for supporting emerging telecom services such as ultra-high-definition video streaming, cloud computing, connected car, virtual/augmented reality, etc., bring to the fore the necessity to upgrade continuously the technology behind transport networks in order to keep pace with this exponential traffic growth. Thus, everything seems to indicate that fixed-grid Wavelength-Division Multiplexed (WDM) networks will be upgraded by adopting a flexible-grid, thus providing finer bandwidth allocation granularities, and therefore, increasing the Grade-of-Service by packing more information in the same spectral band of standard Single-Mode Fibers (SMFs). Nevertheless, unfortunately, the fundamental Shannon’s limit of SMFs is rapidly approaching, and, then, the research efforts to increase the SMFs' capacity will be useless. One solution to overcome this capacity crunch effect is to enable one extra dimension in addition to the frequency one, namely, the spatial dimension, thus deploying S parallel paths in order to multiply, in the best case, by S the capacity of SMF-based networks. However, additionally, it is necessary to decrease the cost and energy per bit in order to provide economically attractive solutions. For this purpose, a smooth upgrade path has to be carried out as new integrated devices and system components are developed for Space Division Multiplexing (SDM). This thesis is concentrated on the planning and operation of the combined flexible WDM and SDM networks (i.e., Flex-Grid/SDM networks) proposing several strategies aimed at optimizing network resources usage with hardware complexity analysis. For this purpose, firstly, network problems are carefully studied and stated, and then, mathematical and/or heuristic algorithms are designed and implemented in an optical network simulator. Specifically, after an introduction to the thesis, chapter 2 presents the background and related work. Next, chapter 3 concentrates on the study of spatially fixed Flex-Grid/SDM networks, i.e., when a rigid number of spatial channels are reserved per allocated traffic demand. In its turn, chapter 4 studies the case of Spectrally-Spatially Flexible Optical Networks (SS-FONs), as the ones providing the upper-bound network capacity. Costs and hardware requirements implied on providing this flexibility are analyzed. Network nodes aimed at reducing the cost of SS-FONs are presented and evaluated in chapter 5. Finally, this thesis ends with the presentation of the main contributions and future research work in chapter 6.La demanda de ancho de banda cada vez más exigente para soportar servicios de telecomunicación emergentes tales como la transmisión de video de alta calidad, computación en la nube, vehículo conectado, realidad virtual/aumentada, etc.…, ha puesto de manifiesto la necesidad de actualizar constantemente la tecnología detrás de las redes de transporte óptico con la finalidad de ir a la par de este incremento exponencial del tráfico. De esta manera, todo parece indicar que las redes basadas en la multiplexación por division de longitud de onda (Wavelength Division Multiplexing, WDM) de ancho espectral fijo serán actualizadas adoptando un ancho de banda espectral flexible, que ofrece asignaciones de ancho de banda con granularidad más fina acorde a las demandas de tráfico; y por lo tanto, incremanta el Grado de Servicio de la red, ya que se permite acomodar mayor información en la misma banda espectral de las fibras monomodo (Single Mode Fibers, SMFs). Sin embargo, desafortunadamente, el límite de Shannon de las fibras monomodo se está aproximando cada vez más, y cuando esto ocurra las investigaciones para incrementar la capacidad de las fibras monomodo serán infructuosas. Una posible solución para superar este colapso de las fibras monomodo es habilitar la dimensión espacial a más de la frecuencial, desplegando � caminos paralelos con la finalidad de multiplicar por � (en el mejor de los casos) la capacidad de las fibras monomodo. No obstante, es necesario disminuir el costo y la energía por bit con la finalidad de proveer soluciones comerciales atractivas. Para tal propósito debe llevarse a cabo una actualización moderada conforme nuevos dispositivos y componentes integrados son desarrollados para la implementación de la tecnología basada en la multiplexación por división de espacio (Space Division Multiplexing, SDM). Esta tesis se concentra en la planificación y operación de la combinación de las redes WDM flexibles y SDM (es decir, de las redes Flex-Grid/SDM) proponiendo varias estrategias dirigidas a optimizar el uso de los recursos de red junto con el análisis de la complejidad del hardware que viene acompañada. Para este fin, primeramente, los problemas de red son cuidadosamente estudiados y descritos. A continuación, se han diseñado e implementado algoritmos basados en programación lineal entera o heurísticas en un simulador de redes ópticas. Después de una introducción inicial, el capítulo 2 de esta tesis presenta el marco teórico sobre los conceptos tratados y los trabajos publicados anteriormente. A continuación, el capítulo 3 se concentra en el estudio de las redes Flex-Grid/SDM con la dimensión espacial rígida; es decir, cuando un número fijo de canales espaciales son reservados por cada demanda de tráfico establecida. Por su parte, el capítulo 4 estudia las redes Flex-Grid/SDM considerando flexibilidad tanto en el dominio espacial como espectral (Spectrally and Spatially Flexible Optical Networks, SS-FONs), las cuales proveerían la capacidad máxima de las redes SDM. Adicionalmente, los costos y requerimientos de hardware implicados en la provisión de esta flexibilidad son analizados. El capítulo 5 presenta la evaluación de nodos orientados a reducir los costos de las SS-FONs. Finalmente, el capítulo 6 expone las principales contribuciones y las posibles líneas de trabajo futuroEls requisits incessants d’ample de banda per al suport de nous serveis de telecomunicació, com poden ser la difusió en directe de vídeo de molt alta definició, la informàtica en el núvol, els cotxes intel·ligents connectats a la xarxa, la realitat virtual/augmentada, etc…, han exigit una millora contínua de les tecnologíes de les actuals xarxes de transport de dades. Tot sembla indicar que les xarxes de transport òptiques actuals, basades en la tecnologia de multiplexació per divisió de longitud d’ona (Wavelength Division Multiplexing, WDM) sobre un grid espectral rígid, hauran de ser reemplaçades per tecnologies òptiques més flexibles, amb una granularitat més fina a l’hora de suportar noves connexions, incrementat el grau de servei de les xarxes gràcies a aprofitament major de l’ample de banda espectral proporcionat per les fibres òptiques monomode (Single Mode Fibers, SMFs). Tanmateix, estem exhaurint ja la capacitat màxima de les fibres òptiques SMF segons ens indica el límit fonamental de Shannon. Per tant, qualsevol esforç enfocat a millorar la capacitat d’aquestes xarxes basades en SMFs pot acabar sent infructuós. Una possible solució per superar aquestes limitacions de capacitat és explorar la dimensió espacial, a més de l’espectral, desplegant camins en paral·lel per tal de multiplicar per , en el millor cas, la capacitat de les SMFs. Tot i això, és necessari reduir el cost i el consum energètic per bit transmès, per tal de proporcionar solucions econòmicament viables. Amb aquest propòsit, pot ser necessària una migració progressiva, a mesura que es desenvolupen nous dispositius i components per aquesta nova tecnologia de multiplexació per divisió espacial (Spatial Division Multiplexing, SDM). La present tesi es centra en la planificació i operació de xarxes òptiques de nova generació que combinin tecnologies de xarxa WDM flexible i SDM (és a dir, xarxes Flex-Grid/SDM), proposant estratègies per a l’optimització de l’ús dels recursos de xarxa i, en definitiva, el seu cost (CapEx). Amb aquest propòsit, s’analitzen en primer moment els problemes adreçats. Tot seguit, es dissenyen algorismes per tal de solucionar-los, basats en tècniques de programació matemàtica i heurístiques, els quals s’implementen i es proven en un simulador de xarxa òptica. Després d’una introducció inicial, el capítol 2 d’aquesta tesi presenta tots els conceptes tractats i treballs relacionats publicats amb anterioritat. Tot seguit, el capítol 3 es centra en l’estudi de les xarxes Flex-Grid/SDM fixes en el domini espai, és a dir, on sempre es reserva un nombre rígid de canals espacials per qualsevol demanda suportada. El capítol 4 estudia les xarxes flexibles en els dominis espectrals i espacials (Spectrally-Spatially Flexible Optical Nextworks, SS-FONs), com aquelles que poden proporcionar una capacitat de xarxa màxima. En aquest context, s’analitzen els requeriments en termes de cost i hardware per tal de proporcionar aquesta flexibilitat. Llavors, en el capítol 6 es presenten opcions de node de xarxa capaces de reduir els costos de les xarxes SS-FONs. Finalment, en el capítol 7 es repassen totes les contribucions de la tesi, així com posibles línies de treball futurAward-winningPostprint (published version

Dual-Stage Planning for Elastic Optical Networks Integrating Machine-Learning-Assisted QoT Estimation

Following the emergence of Elastic Optical Networks (EONs), Machine Learning (ML) has been intensively investigated as a promising methodology to address complex network management tasks, including, e.g., Quality of Transmission (QoT) estimation, fault management, and automatic adjustment of transmission parameters. Though several ML-based solutions for specific tasks have been proposed, how to integrate the outcome of such ML approaches inside Routing and Spectrum Assignment (RSA) models (which address the fundamental planning problem in EONs) is still an open research problem. In this study, we propose a dual-stage iterative RSA optimization framework that incorporates the QoT estimations provided by a ML regressor, used to define lightpaths' reach constraints, into a Mixed Integer Linear Programming (MILP) formulation. The first stage minimizes the overall spectrum occupation, whereas the second stage maximizes the minimum inter-channel spacing between neighbor channels, without increasing the overall spectrum occupation obtained in the previous stage. During the second stage, additional interference constraints are generated, and these constraints are then added to the MILP at the next iteration round to exclude those lightpaths combinations that would exhibit unacceptable QoT. Our illustrative numerical results on realistic EON instances show that the proposed ML-assisted framework achieves spectrum occupation savings up to 52.4% (around 33% on average) in comparison to a traditional MILP-based RSA framework that uses conservative reach constraints based on margined analytical models

Artificial intelligence (AI) methods in optical networks: A comprehensive survey

Producción CientíficaArtificial intelligence (AI) is an extensive scientific discipline which enables computer systems to solve problems by emulating complex biological processes such as learning, reasoning and self-correction. This paper presents a comprehensive review of the application of AI techniques for improving performance of optical communication systems and networks. The use of AI-based techniques is first studied in applications related to optical transmission, ranging from the characterization and operation of network components to performance monitoring, mitigation of nonlinearities, and quality of transmission estimation. Then, applications related to optical network control and management are also reviewed, including topics like optical network planning and operation in both transport and access networks. Finally, the paper also presents a summary of opportunities and challenges in optical networking where AI is expected to play a key role in the near future.Ministerio de Economía, Industria y Competitividad (Project EC2014-53071-C3-2-P, TEC2015-71932-REDT

Physical Layer Aware Optical Networks

This thesis describes novel contributions in the field of physical layer aware optical networks. IP traffic increase and revenue compression in the Telecom industry is putting a lot of pressure on the optical community to develop novel solutions that must both increase total capacity while being cost effective. This requirement is pushing operators towards network disaggregation, where optical network infrastructure is built by mix and match different physical layer technologies from different vendors. In such a novel context, every equipment and transmission technique at the physical layer impacts the overall network behavior. Hence, methods giving quantitative evaluations of individual merit of physical layer equipment at network level are a firm request during network design phases as well as during network lifetime. Therefore, physical layer awareness in network design and operation is fundamental to fairly assess the potentialities, and exploit the capabilities of different technologies. From this perspective, propagation impairments modeling is essential. In this work propagation impairments in transparent optical networks are summarized, with a special focus on nonlinear effects. The Gaussian Noise model is reviewed, then extended for wideband scenarios. To do so, the impact of polarization mode dispersion on nonlinear interference (NLI) generation is assessed for the first time through simulation, showing its negligible impact on NLI generation. Thanks to this result, the Gaussian Noise model is generalized to assess the impact of space and frequency amplitude variations along the fiber, mainly due to stimulated Raman scattering, on NLI generation. The proposed Generalized GN (GGN) model is experimentally validated on a setup with commercial linecards, compared with other modeling options, and an example of application is shown. Then, network-level power optimization strategies are discussed, and the Locally Optimization Global Optimization (LOGO) approach reviewed. After that, a novel framework of analysis for optical networks that leverages detailed propagation impairment modeling called the Statistical Network Assessment Process (SNAP) is presented. SNAP is motivated by the need of having a general framework to assess the impact of different physical layer technologies on network performance, without relying on rigid optimization approaches, that are not well-suited for technology comparison. Several examples of applications of SNAP are given, including comparisons of transceivers, amplifiers and node technologies. SNAP is also used to highlight topological bottlenecks in progressively loaded network scenarios and to derive possible solutions for them. The final work presented in this thesis is related to the implementation of a vendor agnostic quality of transmission estimator for multi-vendor optical networks developed in the context of the Physical Simulation Environment group of the Telecom Infra Project. The implementation of a module based on the GN model is briefly described, then results of a multi-vendor experimental validation performed in collaboration with Microsoft are shown

Scheduling algorithms for throughput maximization in data networks

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2007.Includes bibliographical references (p. 215-226).This thesis considers the performance implications of throughput optimal scheduling in physically and computationally constrained data networks. We study optical networks, packet switches, and wireless networks, each of which has an assortment of features and constraints that challenge the design decisions of network architects. In this work, each of these network settings are subsumed under a canonical model and scheduling framework. Tools of queueing analysis are used to evaluate network throughput properties, and demonstrate throughput optimality of scheduling and routing algorithms under stochastic traffic. Techniques of graph theory are used to study network topologies having desirable throughput properties. Combinatorial algorithms are proposed for efficient resource allocation. In the optical network setting, the key enabling technology is wavelength division multiplexing (WDM), which allows each optical fiber link to simultaneously carry a large number of independent data streams at high rate. To take advantage of this high data processing potential, engineers and physicists have developed numerous technologies, including wavelength converters, optical switches, and tunable transceivers.(cont.) While the functionality provided by these devices is of great importance in capitalizing upon the WDM resources, a major challenge exists in determining how to configure these devices to operate efficiently under time-varying data traffic. In the WDM setting, we make two main contributions. First, we develop throughput optimal joint WDM reconfiguration and electronic-layer routing algorithms, based on maxweight scheduling. To mitigate the service disruption associated with WDM reconfiguration, our algorithms make decisions at frame intervals. Second, we develop analytic tools to quantify the maximum throughput achievable in general network settings. Our approach is to characterize several geometric features of the maximum region of arrival rates that can be supported in the network. In the packet switch setting, we observe through numerical simulation the attractive throughput properties of a simple maximal weight scheduler. Subsequently, we consider small switches, and analytically demonstrate the attractive throughput properties achievable using maximal weight scheduling. We demonstrate that such throughput properties may not be sustained in larger switches.(cont.) In the wireless network setting, mesh networking is a promising technology for achieving connectivity in local and metropolitan area networks. Wireless access points and base stations adhering to the IEEE 802.11 wireless networking standard can be bought off the shelf at little cost, and can be configured to access the Internet in minutes. With ubiquitous low-cost Internet access perceived to be of tremendous societal value, such technology is naturally garnering strong interest. Enabling such wireless technology is thus of great importance. An important challenge in enabling mesh networks, and many other wireless network applications, results from the fact that wireless transmission is achieved by broadcasting signals through the air, which has the potential for interfering with other parts of the network. Furthermore, the scarcity of wireless transmission resources implies that link activation and packet routing should be effected using simple distributed algorithms. We make three main contributions in the wireless setting. First, we determine graph classes under which simple, distributed, maximal weight schedulers achieve throughput optimality.(cont.) Second, we use this acquired knowledge of graph classes to develop combinatorial algorithms, based on matroids, for allocating channels to wireless links, such that each channel can achieve maximum throughput using simple distributed schedulers. Third, we determine new conditions under which distributed algorithms for joint link activation and routing achieve throughput optimality.by Andrew Brzezinski.Ph.D

Efficient Spectrum Utilization in Large-Scale RWA and RSA Problems

While the Routing and Wavelength Assignment (RWA) problem has been widely studied, very few studies attempt to solve realistic size instances, namely, with 100 wavelengths per fiber and a few hundred nodes. Indeed, state of the art is closer to around 20 nodes and 30 wavelengths. In this study, we are interested in reducing the gap between realistic data sets and testbed instances, using exact methods. We propose different algorithms that lead to solve exactly or near exactly much larger instances than in the literature, with up to 150 wavelengths and 90 nodes. Extensive numerical experiences are conducted on both the static and the dynamic cases. For the latter, we investigate how much bandwidth is wasted when no lightpath re-arrangement is allowed, and compare it with the number of lightpath re-arrangement it requires in order to fully maximize the grade of service. Results show that the amount of lightpath re-arrangement remains very small in comparison to the amount of wasted bandwidth if not done. The Routing and Spectrum Assignment (RSA) problem is a much more difficult problem than RWA, considered in elastic optical networks. Although investigated extensively, there is still a gap between the size of the instances that can be solved using the current heuristic or exact algorithms, and the size of the instances arising in the industry. As the second objective of this study, we aim to reduce the gap between the two, using a new mathematical modeling, and compare its performance with the best previous algorithms/models on realistic data instances