82 research outputs found

    Maximizing Revenue With Adaptive Modulation and Multiple FECs in Flexible Optical Networks

    Get PDF
    Flexible optical networks (FONs) are being adopted to accommodate the increasingly heterogeneous traffic in today's Internet. However, in presence of high traffic load, not all offered traffic can be satisfied at all time. As carried traffic load brings revenues to operators, traffic blocking due to limited spectrum resource leads to revenue losses. In this study, given a set of traffic requests to be provisioned, we consider the problem of maximizing operator's revenue, subject to limited spectrum resource and physical layer impairments (PLIs), namely amplified spontaneous emission noise (ASE), self-channel interference (SCI), cross-channel interference (XCI), and node crosstalk. In FONs, adaptive modulation, multiple FEC, and the tuning of power spectrum density (PSD) can be effectively employed to mitigate the impact of PLIs. Hence, in our study, we propose a universal bandwidth-related impairment evaluation model based on channel bandwidth, which allows a performance analysis for different PSD, FEC and modulations. Leveraging this PLI model and a piecewise linear fitting function, we succeed to formulate the revenue maximization problem as a mixed integer linear program. Then, to solve the problem on larger network instances, a fast two-phase heuristic algorithm is also proposed, which is shown to be near-optimal for revenue maximization. Through simulations, we demonstrate that using adaptive modulation enables to significantly increase revenues in the scenario of high signal-to-noise ratio (SNR), where the revenue can even be doubled for high traffic load, while using multiple FECs is more profitable for scenarios with low SNR

    Throughput Maximization Leveraging Just-Enough SNR Margin and Channel Spacing Optimization

    Full text link
    Flexible optical network is a promising technology to accommodate high-capacity demands in next-generation networks. To ensure uninterrupted communication, existing lightpath provisioning schemes are mainly done with the assumption of worst-case resource under-provisioning and fixed channel spacing, which preserves an excessive signal-to-noise ratio (SNR) margin. However, under a resource over-provisioning scenario, the excessive SNR margin restricts the transmission bit-rate or transmission reach, leading to physical layer resource waste and stranded transmission capacity. To tackle this challenging problem, we leverage an iterative feedback tuning algorithm to provide a just-enough SNR margin, so as to maximize the network throughput. Specifically, the proposed algorithm is implemented in three steps. First, starting from the high SNR margin setup, we establish an integer linear programming model as well as a heuristic algorithm to maximize the network throughput by solving the problem of routing, modulation format, forward error correction, baud-rate selection, and spectrum assignment. Second, we optimize the channel spacing of the lightpaths obtained from the previous step, thereby increasing the available physical layer resources. Finally, we iteratively reduce the SNR margin of each lightpath until the network throughput cannot be increased. Through numerical simulations, we confirm the throughput improvement in different networks and with different baud-rates. In particular, we find that our algorithm enables over 20\% relative gain when network resource is over-provisioned, compared to the traditional method preserving an excessive SNR margin.Comment: submitted to IEEE JLT, Jul. 17th, 2021. 14 pages, 8 figure

    Enabling Technologies for Cognitive Optical Networks

    Get PDF

    Autonomous and reliable operation of multilayer optical networks

    Get PDF
    This Ph.D. thesis focuses on the reliable autonomous operation of multilayer optical networks. The first objective focuses on the reliability of the optical network and proposes methods for health analysis related to Quality of Transmission (QoT) degradation. Such degradation is produced by soft-failures in optical devices and fibers in core and metro segments of the operators’ transport networks. Here, we compare estimated and measured QoT in the optical transponder by using a QoT tool based on GNPy. We show that the changes in the values of input parameters of the QoT model representing optical devices can explain the deviations and degradation in performance of such devices. We use reverse engineering to estimate the value of those parameters that explain the observed QoT. We show by simulation a large anticipation in soft-failure detection, localization and identification of degradation before affecting the network. Finally, for validating our approach, we experimentally observe the high accuracy in the estimation of the modeling parameters. The second objective focuses on multilayer optical networks, where lightpaths are used to connect packet nodes thus creating virtual links (vLink). Specifically, we study how lightpaths can be managed to provide enough capacity to the packet layer without detrimental effects in their Quality of Service (QoS), like added delays or packet losses, and at the same time minimize energy consumption. Such management must be as autonomous as possible to minimize human intervention. We study the autonomous operation of optical connections based on digital subcarrier multiplexing (DSCM). We propose several solutions for the autonomous operation of DSCM systems. In particular, the combination of two modules running in the optical node and in the optical transponder activate and deactivate subcarriers to adapt the capacity of the optical connection to the upper layer packet traffic. The module running in the optical node is part of our Intent-based Networking (IBN) solution and implements prediction to anticipate traffic changes. Our comprehensive study demonstrates the feasibility of DSCM autonomous operation and shows large cost savings in terms of energy consumption. In addition, our study provides a guideline to help vendors and operators to adopt the proposed solutions. The final objective targets at automating packet layer connections (PkC). Automating the capacity required by PkCs can bring further cost reduction to network operators, as it can limit the resources used at the optical layer. However, such automation requires careful design to avoid any QoS degradation, which would impact Service Level Agreement (SLA) in the case that the packet flow is related to some customer connection. We study autonomous packet flow capacity management. We apply RL techniques and propose a management lifecycle consisting of three different phases: 1) a self-tuned threshold-based approach for setting up the connection until enough data is collected, which enables understanding the traffic characteristics; 2) RL operation based on models pre-trained with generic traffic profiles; and 3) RL operation based on models trained with the observed traffic. We show that RL algorithms provide poor performance until they learn optimal policies, as well as when the traffic characteristics change over time. The proposed lifecycle provides remarkable performance from the starting of the connection and it shows the robustness while facing changes in traffic. The contribution is twofold: 1) and on the one hand, we propose a solution based on RL, which shows superior performance with respect to the solution based on prediction; and 2) because vLinks support packet connections, coordination between the intents of both layers is proposed. In this case, the actions taken by the individual PkCs are used by the vLink intent. The results show noticeable performance compared to independent vLink operation.Esta tesis doctoral se centra en la operación autónoma y confiable de redes ópticas multicapa. El primer objetivo se centra en la fiabilidad de la red óptica y propone métodos para el análisis del estado relacionados con la degradación de la calidad de la transmisión (QoT). Dicha degradación se produce por fallos en dispositivos ópticos y fibras en las redes de transporte de los operadores que no causan el corte de la señal. Comparamos el QoT estimado y medido en el transpondedor óptico mediante el uso de una herramienta de QoT basada en GNPy. Mostramos que los cambios en los valores de los parámetros de entrada del modelo QoT que representan los dispositivos ópticos pueden explicar las desviaciones y la degradación en el rendimiento de dichos dispositivos. Usamos ingeniería inversa para estimar el valor de aquellos parámetros que explican el QoT observado. Mostramos, mediante simulación, una gran anticipación en la detección, localización e identificación de fallas leves antes de afectar la red. Finalmente, validamos nuestro método de forma experimental y comprobamos la alta precisión en la estimación de los parámetros de los modelos. El segundo objetivo se centra en las redes ópticas multicapa, donde se utilizan conexiones ópticas (lightpaths) para conectar nodos de paquetes creando así enlaces virtuales (vLink). Específicamente, estudiamos cómo se pueden gestionar los lightpaths para proporcionar suficiente capacidad a la capa de paquetes sin efectos perjudiciales en su calidad de servicio (QoS), como retrasos adicionales o pérdidas de paquetes, y al mismo tiempo minimizar el consumo de energía. Estudiamos el funcionamiento autónomo de conexiones ópticas basadas en multiplexación de subportadoras digitales (DSCM) y proponemos soluciones para su funcionamiento autónomo. En particular, la combinación de dos módulos que se ejecutan en el nodo óptico y en el transpondedor óptico activan y desactivan subportadoras para adaptar la capacidad de la conexión óptica al tráfico de paquetes. El módulo que se ejecuta en el nodo óptico implementa la predicción para anticipar los cambios de tráfico. Nuestro estudio demuestra la viabilidad de la operación autónoma de DSCM y muestra un gran ahorro de consumo de energía. El objetivo final es la automatización de conexiones de capa de paquete (PkC). La automatización de la capacidad requerida por las PkC puede generar una mayor reducción de costes, ya que puede limitar los recursos utilizados en la capa óptica. Sin embargo, dicha automatización requiere un diseño cuidadoso para evitar cualquier degradación de QoS, lo que afectaría acuerdos de nivel de servicio (SLA) en el caso de que el flujo de paquetes esté relacionado con alguna conexión del cliente. Estudiamos la gestión autónoma de la capacidad del flujo de paquetes. Aplicamos RL y proponemos un ciclo de vida de gestión con tres fases: 1) un enfoque basado en umbrales auto ajustados para configurar la conexión hasta que se recopilen suficientes datos, lo que permite comprender las características del tráfico; 2) operación RL basada en modelos pre-entrenados con perfiles de tráfico genéricos; y 3) operación de RL en base a modelos entrenados con el tránsito observado. Mostramos que los algoritmos de RL ofrecen un desempeño deficiente hasta que aprenden las políticas óptimas, así cuando las características del tráfico cambian con el tiempo. El ciclo de vida propuesto proporciona un rendimiento notable desde el inicio de la conexión y muestra la robustez frente a cambios en el tráfico. La contribución es doble: 1) proponemos una solución basada en RL que muestra un rendimiento superior que la solución basada en predicción; y 2) debido a que los vLinks admiten conexiones de paquetes, se propone la coordinación entre las intenciones de ambas capas. En este caso, la intención de vLink utiliza las acciones realizadas por los PkC individuales. Los resultados muestran un rendimiento notable en comparación con la operación independiente de vLink.Postprint (published version

    Exploiting optical signal analysis for autonomous communications

    Get PDF
    (English) Optical communications have been extensively investigated and enhanced in the last decades. Nowadays, they are responsible to transport all the data traffic generated around the world, from access to the core network segments. As the data traffic is increasing and changing in both type and patterns, the optical communications networks and systems need to readapt and continuous advances to face the future data traffic demands in an efficient and cost-effective way. This PhD thesis focuses on investigate and analyze the optical signals in order to extract useful knowledge from them to support the autonomous lightpath operation, as well as to lightpath characterization. The first objective of this PhD thesis is to investigate the optical transmission feasibility of optical signals based on high-order modulation formats (MF) and high symbol rates (SR) in hybrid filterless, filtered and flexible optical networks. It is expected a higher physical layer impairments impact on these kinds of optical signals that can lead to degradation of the quality of transmission. In particular, the impact of the optical filter narrowing arising from the node cascade is evaluated. The obtained simulation results for the required optical-signal-to-noise ratio in a cascade up to 10 optical nodes foresee the applicability of these kinds of optical signals in such scenarios. By using high-order MF and high SR, the number of the optical transponders cab be reduced, as well as the spectral efficiency is enhanced. The second objective focuses on MF and SR identification at the optical receiver side to support the autonomous lightpath operation. Nowadays, optical transmitters can generate several optical signal configurations in terms of MF and SR. To increase the autonomous operation of the optical receiver, it is desired it can autonomously recognize the MF and SR of the incoming optical signals. In this PhD thesis, we propose an accurate and low complex MF and SR identification algorithm based on optical signal analysis and minimum Euclidean distance to the expected points when the received signals are decoded with several available MF and SR. The extensive simulation results show remarkable accuracy under several realistic lightpath scenarios, based on different fiber types, including linear and nonlinear noise interference, as well as in single and multicarrier optical systems. The final objective of this PhD thesis is the deployment of a machine learning-based digital twin for optical constellations analysis and modeling. An optical signal along its lightpath in the optical network is impaired by several effects. These effects can be linear, e.g., the noise coming from the optical amplification, or nonlinear ones, e.g., the Kerr effects from the fiber propagation. The optical constellations are a good source of information regarding these effects, both linear and nonlinear. Thus, by an accurate and deep analysis of the received optical signals, visualized in optical constellations, we can extract useful information from them to better understand the several impacts along the crossed lightpath. Furthermore, by learning the different impacts from different optical network elements on the optical signal, we can accurately model it in order to create a partial digital twin of the optical physical layer. The proposed digital twin shows accurate results in modeled lightpaths including both linear and nonlinear interference noise, in several lightpaths configuration, i.e., based on different kind of optical links, optical powers and optical fiber parameters. In addition, the proposed digital twin can be useful to predict quality of transmission metrics, such as bit error rate, in typical lightpath scenarios, as well as to detect possible misconfigurations in optical network elements by cooperation with the software-defined networking controller and monitoring and data analytics agents.(Español) Las comunicaciones ópticas han sido ampliamente investigadas y mejoradas en las últimas décadas. En la actualidad, son las encargadas de transportar la mayoría del tráfico de datos que se genera en todo el mundo, desde el acceso hasta los segmentos de la red troncal. A medida que el tráfico de datos aumenta y cambia tanto en tipo como en patrones, las redes y los sistemas de comunicaciones ópticas necesitan readaptarse y avanzar continuamente para, de una manera eficiente y rentable, hacer frente a las futuras demandas de tráfico de datos. Esta tesis doctoral se centra en investigar y analizar las señales ópticas con el fin de extraer de ellas conocimiento útil para apoyar el funcionamiento autónomo de las conexiones ópticas, así como para su caracterización. El primer objetivo de esta tesis doctoral es investigar la viabilidad de transmisión de señales ópticas basadas en formatos de modulación de alto orden y altas tasas de símbolos en redes ópticas híbridas con y sin filtros. Se espera un mayor impacto de las degradaciones de la capa física en este tipo de señales ópticas que pueden conducir a la degradación de la calidad de transmisión. En particular, se evalúa el impacto de la reducción del ancho de banda del filtro óptico que surge tras atravesar una cascada de nodos. Los resultados de simulación obtenidos para la relación señal óptica/ruido requerida en una cascada de hasta 10 nodos ópticos prevén la aplicabilidad de este tipo de señales ópticas en tales escenarios. Mediante el uso de modulación de alto orden y altas tasas de símbolos, se reduce el número de transpondedores ópticos y se mejora la eficiencia espectral. El segundo objetivo se centra en la identificación de formatos de modulación y tasas de símbolos en el lado del receptor óptico para respaldar la operación autónoma de la conexión óptica. Para aumentar el funcionamiento autónomo del receptor óptico, se desea que pueda reconocer de forma autónoma la configuración de las señales ópticas entrantes. En esta tesis doctoral, proponemos un algoritmo de identificación de formatos de modulación y tasas de símbolos preciso y de baja complejidad basado en el análisis de señales ópticas cuando las señales recibidas se decodifican con varios formatos de modulación y tasas de símbolos disponibles. Los extensos resultados de la simulación muestran una precisión notable en varios escenarios realistas, basados en diferentes tipos de fibra, incluida la interferencia de ruido lineal y no lineal, así como en sistemas ópticos de portadora única y múltiple. El objetivo final de esta tesis doctoral es el despliegue de un gemelo digital basado en aprendizaje automático para el análisis y modelado de constelaciones ópticas. Una señal óptica a lo largo de su trayectoria en la red óptica se ve afectada por varios efectos, pueden ser lineales o no lineales. Las constelaciones ópticas son una buena fuente de información sobre estos efectos, tanto lineales como no lineales. Por lo tanto, mediante un análisis preciso y profundo de las señales ópticas recibidas, visualizadas en constelaciones ópticas, podemos extraer información útil de ellas para comprender mejor los diversos impactos a lo largo del camino propagado. Además, al aprender los diferentes impactos de los diferentes elementos de la red óptica en la señal óptica, podemos modelarla con precisión para crear un gemelo digital parcial de la camada física óptica. El gemelo digital propuesto muestra resultados precisos en conexiones que incluyen ruido de interferencia tanto lineal como no lineal, en varias configuraciones basados en diferentes tipos de enlaces ópticos, potencias ópticas y parámetros de fibra óptica. Además, el gemelo digital propuesto puede ser útil para predecir la calidad de las métricas de transmisión así como para detectar posibles errores de configuración en los elementos de la red óptica mediante la cooperación con el controlador de red, el monitoreo y agentes de análisis de datosPostprint (published version

    CO-OFDM Elastic Optical Networks - Issues on Transmission, Routing, and Bandwidth Allocation

    Get PDF
    The use of orthogonal frequency division multiplexing (OFDM) technology helps an optical transmission system to break the limitation of wavelength grids by wavelength division multiplexing (WDM), in which a flexible and elastic transmission paradigm is created, so as to achieve better energy and spectrum efficiency and flexibility of the fiber resource. By jointly considering the nonlinear effect of Mach-Zehnder modulator (MZM) and amplified spontaneous emission (ASE) noise, we first provide an analytical model on the bit error rate (BER) performance for a single elastic optical transmission line. A novel adaptive transmission strategy in OFDM-based elastic optical transmission systems is proposed. Based on the adaptive transmission strategy, an optimization problem is formulated and solved via mathematical programming. By using proposed adaptive transmission strategy, the routing and bandwidth allocation (RBA) problem is formulated in elastic optical networks and numerically solved to route a set of lightpaths into a network according to the static or dynamic traffic demands with the best energy efficiency, where the laser transmit power, modulation level, number of subcarriers, and routing path of each node pair, are jointly determined. Case studies via extensive numerical experiments are conducted to verify the proposed strategy and gain better understanding on the solutions of formulated optimization problem. By further extending proposed adaptive transmission strategy, we propose a novel adaptive radio-over-fiber (RoF) transmission system for next-generation cloud radio access network (C-RAN). By considering nonlinear distortion from both MZM and high power amplifier (HPA), a 2 x 2 MIMO-OFDM baseband model for simulating the required ESNR of end-to-end RoF transmission system is developed. The RoF system for current C-RAN and proposed RoF system for future C-RAN are presented. We also propose a model to analyze the power consumption for the optical part of RoF transmission system. By performing case studies, proposed RoF system is demonstrated to be more energy efficient than current RoF system.4 month

    Design, monitoring and performance evaluation of high capacity optical networks

    Get PDF
    Premi Extraordinari de Doctorat, promoció 2018-2019. Àmbit de les TICInternet traffic is expected to keep increasing exponentially due to the emergence of a vast number of innovative online services and applications. Optical networks, which are the cornerstone of the underlying Internet infrastructure, have been continuously evolving to carry the ever-increasing traffic in a more flexible, cost-effective, and intelligent way. Having these three targets in mind, this PhD thesis focuses on two general areas for the performance improvement and the evolution of optical networks: i) introducing further cognition to the optical layer, and ii) introducing new networking solutions revolutionizing the optical transport infrastructure. In the first part, we present novel failure detection and identification solutions in the optical layer utilizing the optical spectrum traces captured by cost-effective coarse-granular Optical Spectrum Analyzers (OSA). We demonstrate the effectiveness of the developed solutions for detecting and identifying filter-related failures in the context of Spectrum-Switched Optical Networks (SSON), as well as transmitter-related laser failures in Filter-less Optical Networks (FON). In addition, at the subsystem level we propose an Autonomic Transmission Agent (ATA), which triggers local or remote transceiver reconfiguration by predicting Bit-Error-Rate (BER) degradation by monitoring State-of-Polarization (SOP) data obtained by coherent receivers. I have developed solutions to push further the performance of the currently deployed optical networks through reducing the margins and introducing intelligence to better manage their resources. However, it is expected that the spectral efficiency of the current standard Single-Mode Fiber (SMF) based optical network approaches the Shannon capacity limits in the near future, and therefore, a new paradigm is required to keep with the pace of the current huge traffic increase. In this regard, Space Division Multiplexing (SDM) is proposed as the ultimate solution to address the looming capacity crunch with a reduced cost-per-bit delivered to the end-users. I devote the second part of this thesis to investigate different flavors of SDM based optical networks with the aim of finding the best compromise for the realization of a spectrally and spatially flexible optical network. SDM-based optical networks can be deployed over various types of transmission media. Additionally, due to the extra dimension (i.e., space) introduced in SDM networks, optical switching nodes can support wavelength granularity, space granularity, or a combination of both. In this thesis, we evaluate the impact of various spectral and spatial switching granularities on the performance of SDM-based optical networks serving different profiles of traffic with the aim of understanding the impact of switching constraints on the overall network performance. In this regard, we consider two different generations of wavelength selective switches (WSS) to reflect the technology limitations on the performance of SDM networks. In addition, we present different designs of colorless direction-less, and Colorless Directionless Contention-less (CDC) Reconfigurable Optical Add/Drop Multiplexers (ROADM) realizing SDM switching schemes and compare their performance in terms of complexity and implementation cost. Furthermore, with the aim of revealing the benefits and drawbacks of SDM networks over different types of transmission media, we preset a QoT-aware network planning toolbox and perform comparative performance analysis among SDM network based on various types of transmission media. We also analyze the power consumption of Multiple-Input Multiple-Output (MIMO) Digital Signal Processing (DSP) units of transceivers operating over three different types of transmission media. The results obtained in the second part of the thesis provide a comprehensive outlook to different realizations of SDM-based optical networks and showcases the benefits and drawbacks of different SDM realizations.Se espera que el tráfico de Internet siga aumentando exponencialmente debido a la continua aparición de gran cantidad de aplicaciones innovadoras. Las redes ópticas, que son la piedra angular de la infraestructura de Internet, han evolucionado continuamente para transportar el tráfico cada vez mayor de una manera más flexible, rentable e inteligente. Teniendo en cuenta estos tres objetivos, esta tesis doctoral se centra en dos áreas cruciales para la mejora del rendimiento y la evolución de las redes ópticas: i) introducción de funcionalidades cognitivas en la capa óptica, y ii) introducción de nuevas estructuras de red que revolucionarán el transporte óptico. En la primera parte, se presentan soluciones novedosas de detección e identificación de fallos en la capa óptica que utilizan trazas de espectro óptico obtenidas mediante analizadores de espectros ópticos (OSA) de baja resolución (y por tanto de coste reducido). Se demuestra la efectividad de las soluciones desarrolladas para detectar e identificar fallos derivados del filtrado imperfecto en las redes ópticas de conmutación de espectro (SSON), así como fallos relacionados con el láser transmisor en redes ópticas sin filtro (FON). Además, a nivel de subsistema, se propone un Agente de Transmisión Autónomo (ATA), que activa la reconfiguración del transceptor local o remoto al predecir la degradación de la Tasa de Error por Bits (BER), monitorizando el Estado de Polarización (SOP) de la señal recibida en un receptor coherente. Se han desarrollado soluciones para incrementar el rendimiento de las redes ópticas mediante la reducción de los márgenes y la introducción de inteligencia en la administración de los recursos de la red. Sin embargo, se espera que la eficiencia espectral de las redes ópticas basadas en fibras monomodo (SMF) se acerque al límite de capacidad de Shannon en un futuro próximo, y por tanto, se requiere un nuevo paradigma que permita mantener el crecimiento necesario para soportar el futuro aumento del tráfico. En este sentido, se propone el Multiplexado por División Espacial (SDM) como la solución que permita la continua reducción del coste por bit transmitido ante ése esperado crecimiento del tráfico. En la segunda parte de esta tesis se investigan diferentes tipos de redes ópticas basadas en SDM con el objetivo de encontrar soluciones para la realización de redes ópticas espectral y espacialmente flexibles. Las redes ópticas basadas en SDM se pueden implementar utilizando diversos tipos de medios de transmisión. Además, debido a la dimensión adicional (el espacio) introducida en las redes SDM, los nodos de conmutación óptica pueden conmutar longitudes de onda, fibras o una combinación de ambas. Se evalúa el impacto de la conmutación espectral y espacial en el rendimiento de las redes SDM bajo diferentes perfiles de tráfico ofrecido, con el objetivo de comprender el impacto de las restricciones de conmutación en el rendimiento de la red. En este sentido, se consideran dos generaciones diferentes de conmutadores selectivos de longitud de onda (WSS) para reflejar las limitaciones de la tecnología en el rendimiento de las redes SDM. Además, se presentan diferentes diseños de ROADM, independientes de la longitud de onda, de la dirección, y sin contención (CDC) utilizados para la conmutación SDM, y se compara su rendimiento en términos de complejidad y coste. Además, con el objetivo de cuantificar los beneficios e inconvenientes de las redes SDM, se ha generado una herramienta de planificación de red que prevé la QoT usando diferentes tipos de fibras. También se analiza el consumo de energía de las unidades DSP de los transceptores MIMO operando en redes SDM con tres tipos diferentes de medios de transmisión. Los resultados obtenidos en esta segunda parte de la tesis proporcionan una perspectiva integral de las redes SDM y muestran los beneficios e inconvenientes de sus diferentes implementacionesAward-winningPostprint (published version
    corecore