Modeling And Optimization Of Optical Communication Networks

MODELING and OPTIMIZATION of OPTICAL COMMUNICATION NETWORKS Optical networks are an integral part of many of the technologies that we use every day. It is a constantly changing and evolving area, with new materials, processes, and applications coming online almost daily. This book provides a basis for discussing open principles, methods and research problems in the modeling of optical communication networks. It also provides a systematic overview of the state-of-the-art research efforts and potential research directions dealing with optical communication metworks. It also simultaneously focuses on extending the limits of currently used systems encompassing optical and wireless domains and explores novel research on wireless and optical techniques and systems, describing practical implementation activities, results and issues. A handbook on applications for both academia and industry, this exciting new volume includes detailed discussions on real-world case studies on trends and emerging technologies associated with modeling of optical communication networks. This book also describes several numerical models and algorithms for simulation and optimization of optical communication networks. Modeling and optimization presents several opportunities for automating operations and introducing intelligent decision making in network planning and in dynamic control and management of network resources, including issues like connection establishment, self-configuration, and self-optimization, through prediction and estimation by utilizing present network state and historical data. It focuses on extending the limits of currently used systems encompassing optical and wireless domains, and explores the latest developments in applications like photonics, high speed communication systems and networks, visible light communication, nano-photonics, wireless, and MIMO systems.

MODELING and OPTIMIZATION of OPTICAL COMMUNICATION NETWORKS Optical networks are an integral part of many of the technologies that we use every day. It is a constantly changing and evolving area, with new materials, processes, and applications coming online almost daily. This book provides a basis for discussing open principles, methods and research problems in the modeling of optical communication networks. It also provides a systematic overview of the state-of-the-art research efforts and potential research directions dealing with optical communication metworks. It also simultaneously focuses on extending the limits of currently used systems encompassing optical and wireless domains and explores novel research on wireless and optical techniques and systems, describing practical implementation activities, results and issues. A handbook on applications for both academia and industry, this exciting new volume includes detailed discussions on real-world case studies on trends and emerging technologies associated with modeling of optical communication networks. This book also describes several numerical models and algorithms for simulation and optimization of optical communication networks. Modeling and optimization presents several opportunities for automating operations and introducing intelligent decision making in network planning and in dynamic control and management of network resources, including issues like connection establishment, self-configuration, and self-optimization, through prediction and estimation by utilizing present network state and historical data. It focuses on extending the limits of currently used systems encompassing optical and wireless domains, and explores the latest developments in applications like photonics, high speed communication systems and networks, visible light communication, nano-photonics, wireless, and MIMO systems.

Enabling Technologies for High Spectral-efficiency Coherent Optical Communication Networks Presents the technological advancements that enable high spectral-efficiency and high-capacity fiber-optic communication systems and networks This book examines key technology advances in high spectral-efficiency fiber-optic communication systems and networks, enabled by the use of coherent detection and digital signal processing (DSP). The first of this book’s 16 chapters is a detailed introduction. Chapter 2 reviews the modulation formats, while Chapter 3 focuses on detection and error correction technologies for coherent optical communication systems. Chapters 4 and 5 are devoted to Nyquist-WDM and orthogonal frequency-division multiplexing (OFDM). In chapter 6, polarization and nonlinear impairments in coherent optical communication systems are discussed. The fiber nonlinear effects in a non-dispersion-managed system are covered in chapter 7. Chapter 8 describes linear impairment equalization and Chapter 9 discusses various nonlinear mitigation techniques. Signal synchronization is covered in Chapters 10 and 11. Chapter 12 describes the main constraints put on the DSP algorithms by the hardware structure. Chapter 13 addresses the fundamental concepts and recent progress of photonic integration. Optical performance monitoring and elastic optical network technology are the subjects of Chapters 14 and 15. Finally, Chapter 16 discusses spatial-division multiplexing and MIMO processing technology, a potential solution to solve the capacity limit of single-mode fibers. Contains basic theories and up-to-date technology advancements in each chapter Describes how capacity-approaching coding schemes based on low-density parity check (LDPC) and spatially coupled LDPC codes can be constructed by combining iterative demodulation and decoding Demonstrates that fiber nonlinearities can be accurately described by some analytical models, such as GN-EGN model Presents impairment equalization and mitigation techniques Enabling Technologies for High Spectral-efficiency Coherent Optical Communication Networks is a reference for researchers, engineers, and graduate students.

Machine Learning for Future Fiber-Optic Communication Systems provides a comprehensive and in-depth treatment of machine learning concepts and techniques applied to key areas within optical communications and networking, reflecting the state-of-the-art research and industrial practices. The book gives knowledge and insights into the role machine learning-based mechanisms will soon play in the future realization of intelligent optical network infrastructures that can manage and monitor themselves, diagnose and resolve problems, and provide intelligent and efficient services to the end users. With up-to-date coverage and extensive treatment of various important topics related to machine learning for fiber-optic communication systems, this book is an invaluable reference for photonics researchers and engineers. It is also a very suitable text for graduate students interested in ML-based signal processing and networking. Discusses the reasons behind the recent popularity of machine learning (ML) concepts in modern optical communication networks and the why/where/how ML can play a unique role Presents fundamental ML techniques like artificial neural networks (ANNs), support vector machines (SVMs), K-means clustering, expectation-maximization (EM) algorithm, principal component analysis (PCA), independent component analysis (ICA), reinforcement learning, and more Covers advanced deep learning (DL) methods such as deep neural networks (DNNs), convolutional neural networks (CNNs), recurrent neural networks (RNNs), and generative adversarial networks (GANs) Individual chapters focus on ML applications in key areas of optical communications and networking

Optical networks are leaving the labs and becoming a reality. Despite the current crisis of the telecom industry, our everyday life increasingly depends on communication networks for information exchange, medicine, education, data transfer, commerce, and many other endeavours. High capacity links are required by the large futemet traffic demand, and optical networks remain one of the most promising technologies for meeting these needs. WDM systems are today widely deployed, thanks to low-cost at extreme data rates and high reliability of optical components, such as optical amplifiers and fixed/tunable filters and transceivers. Access and metropolitan area networks are increasingly based on optical technologies to overcome the electronic bottleneck at the network edge. Traditional multi-layer architectures, such as the widely deployed IP/ATM/SDH protocol stack, are increasingly based on WDM transport; further efforts are sought to move at the optical layer more of the functionalities available today in higher protocol layers. New components and subsystems for very high speed optical networks offer new design opportunities to network operators and designers. The trends towards dynamically configurable all-optical network infrastructures open up a wide range of new network engineering and design choices, which must face issues such as interoperability and unified control and management.

Next generation optical communication systems will have to transport a significantly increased data volume at a reduced cost per transmitted bit. To achieve these ambitious goals optimum design is crucial in combination with dynamic adaptation to actual traffic demands and improved energy efficiency. In the first part of the book the author elaborates on the design of optical transmission systems. Several methods for efficient numerical simulation are presented ranging from meta-model based optimization to parallelization techniques for solving the nonlinear Schrödinger equation. Furthermore, fast analytical and semi-analytical models are described to estimate the various degradation effects occurring on the transmission line. In the second part of the book operational aspects of optical networks are investigated. Physical layer impairment-aware routing and regenerator placement are studied. Finally, it is analyzed how the energy efficiency of a multi-layer optical core network can be increased by dynamic adaptation to traffic patterns changing in the course of the day.

This book constitutes the refereed proceedings of the 23rd International IFIP conference on Optical Network Design and Modeling, ONDM 2019, held in Athens, Greece, in May 2019. The 39 revised full papers were carefully reviewed and selected from 87 submissions. The papers focus on cutting-edge research in established areas of optical networking as well as their adoption in support of a wide variety of new services and applications. This involves the most recent trends in networking including 5G and beyond, big data and network data analytics, cloud/edge computing, autonomic networking, artificial intelligence assisted networks, secure and resilient networks, that drive the need for increased capacity, efficiency, exibility and adaptability in the functions that the network can perform. In this context new disaggregated optical network architectures were discussed, exploiting and integrating novel multidimensional photonic technology solutions as well as adopting open hardware and software platforms relying on software defined networking (SDN), and network function virtualization (NFV) to allow support of new business models and opportunities.

This book covers the design and optimization of computer networks applying a rigorous optimization methodology, applicable to any network technology. It is organized into two parts. In Part 1 the reader will learn how to model network problems appearing in computer networks as optimization programs, and use optimization theory to give insights on them. Four problem types are addressed systematically – traffic routing, capacity dimensioning, congestion control and topology design. Part 2 targets the design of algorithms that solve network problems like the ones modeled in Part 1. Two main approaches are addressed – gradient-like algorithms inspiring distributed network protocols that dynamically adapt to the network, or cross-layer schemes that coordinate the cooperation among protocols; and those focusing on the design of heuristic algorithms for long term static network design and planning problems. Following a hands-on approach, the reader will have access to a large set of examples in real-life technologies like IP, wireless and optical networks. Implementations of models and algorithms will be available in the open-source Net2Plan tool from which the user will be able to see how the lessons learned take real form in algorithms, and reuse or execute them to obtain numerical solutions. An accompanying link to the author’s own Net2plan software enables readers to produce numerical solutions to a multitude of real-life problems in computer networks (www.net2plan.com).