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

TCP over High Speed Variable Capacity Links: A Simulation Study for Bandwidth Allocation

New optical network technologies provide opportunities for fast, controllable bandwidth management. These technologies can now explicitly provide resources to data paths, creating demand driven bandwidth reservation across networks where an applications bandwidth needs can be meet almost exactly. Dynamic synchronous Transfer Mode (DTM) is a gigabit network technology that provides channels with dynamically adjustable capacity. TCP is a reliable end-to-end transport protocol that adapts its rate to the available capacity. Both TCP and the DTM bandwidth can react to changes in the network load, creating a complex system with inter-dependent feedback mechanisms. The contribution of this work is an assessment of a bandwidth allocation scheme for TCP flows on variable capacity technologies. We have created a simulation environment using ns-2 and our results indicate that the allocation of bandwidth maximises TCP throughput for most flows, thus saving valuable capacity when compared to a scheme such as link over-provisioning. We highlight one situation where the allocation scheme might have some deficiencies against the static reservation of resources, and describe its causes. This type of situation warrants further investigation to understand how the algorithm can be modified to achieve performance similar to that of the fixed bandwidth case

On IP over WDM burst-switched long haul and metropolitan area networks

The IP over Wavelength Division Multiplexing (WDM) network is a natural evolution ushered in by the phenomenal advances in networking technologies and technical breakthroughs in optical communications, fueled by the increasing demand in the reduction of operation costs and the network management complexity. The unprecedented bandwidth provisioning capability and the multi-service supportability of the WDM technology, in synergy with the data-oriented internetworking mechanisms, facilitates a common shared infrastructure for the Next Generation Internet (NGJ). While NGI targets to perform packet processing directly on the optical transport layer, a smooth evolution is critical to success. Intense research has been conducted to design the new generation optical networks that retain the advantages of packet-oriented transport prototypes while rendering elastic network resource utilization and graded levels of service. This dissertation is focused on the control architecture, enabling technologies, and performance analysis of the WDM burst-switched long haul and Metropolitan Area Networks (MANs). Theoretical analysis and simulation results are reported to demonstrate the system performance and efficiency of proposed algorithms. A novel transmission mechanism, namely, the Forward Resource Reservation (ERR) mechanism, is proposed to reduce the end-to-end delay for an Optical Burst Switching (OBS)-based IP over WDM system. The ERR scheme adopts a Linear Predictive Filter and an aggressive reservation strategy for data burst length prediction and resource reservation, respectively, and is extended to facilitate Quality of Service (QoS) differentiation at network edges. The ERR scheme improves the real-time communication services for applications with time constraints without deleterious system costs. The aggressive strategy for channel holding time reservations is proposed. Specifically, two algorithms, the success probability-driven (SPD) and the bandwidth usage-driven (BUD) ones, are proposed for resource reservations in the FRRenabled scheme. These algorithms render explicit control on the latency reduction improvement and bandwidth usage efficiency, respectively, both of which are important figures of performance metrics. The optimization issue for the FRR-enabled system is studied based on two disciplines - addressing the static and dynamic models targeting different desired objectives (in terms of algorithm efficiency and system performance), and developing a \u27\u27crank back\u27\u27 based signaling mechanism to provide bandwidth usage efficiency. The proposed mechanisms enable the network nodes to make intelligent usage of the bandwidth resources. In addition, a new control architecture with enhanced address resolution protocol (E-ARP), burst-based transmission, and hop-based wavelength allocation is proposed for Ethernet-supported IP over WDM MANs. It is verified, via theoretical analysis and simulation results, that the E-ARP significantly reduces the call setup latency and the transmission requirements associated with the address probing procedures; the burst-based transport mechanism improves the network throughput and resource utilization; and the hop-based wavelength allocation algorithm provides bandwidth multiplexing with fairness and high scalability. The enhancement of the Ethernet services, in tandem with the innovative mechanisms in the WDM domain, facilitates a flexible and efficient integration, thus making the new generation optical MAN optimized for the scalable, survivable, and IP-dominated network at gigabit speed possible

Access and metro network convergence for flexible end-to-end network design

This paper reports on the architectural, protocol, physical layer, and integrated testbed demonstrations carried out by the DISCUS FP7 consortium in the area of access - metro network convergence. Our architecture modeling results show the vast potential for cost and power savings that node consolidation can bring. The architecture, however, also recognizes the limits of long-reach transmission for low-latency 5G services and proposes ways to address such shortcomings in future projects. The testbed results, which have been conducted end-to-end, across access - metro and core, and have targeted all the layers of the network from the application down to the physical layer, show the practical feasibility of the concepts proposed in the project

Autonomous and reliable operation of multilayer optical networks

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

Modelling, Dimensioning and Optimization of 5G Communication Networks, Resources and Services

This reprint aims to collect state-of-the-art research contributions that address challenges in the emerging 5G networks design, dimensioning and optimization. Designing, dimensioning and optimization of communication networks resources and services have been an inseparable part of telecom network development. The latter must convey a large volume of traffic, providing service to traffic streams with highly differentiated requirements in terms of bit-rate and service time, required quality of service and quality of experience parameters. Such a communication infrastructure presents many important challenges, such as the study of necessary multi-layer cooperation, new protocols, performance evaluation of different network parts, low layer network design, network management and security issues, and new technologies in general, which will be discussed in this book

Machine Learning for Multi-Layer Open and Disaggregated Optical Networks

L'abstract è presente nell'allegato / the abstract is in the attachmen