New generation applications, such as cloud computing or video distribution, can run in a telecom cloud infrastructure where the datacenters (DCs) of telecom operators are integrated in their networks thus, increasing connections' dynamicity and resulting in time-varying traffic capacities, which might also entail changes in the traffic direction along the day. As a result, a flexible optical technology able to dynamically set-up variable-capacity connections, such as flexgrid, is needed. Nonetheless, network dynamicity might entail network performance degradation thus, requiring re-optimizing the network while it is in operation. This thesis is devoted to devise new algorithms to solve in-operation network planning problems aiming at enhancing the performance of optical networks and at studying their feasibility in experimental environments. In-operation network planning requires from an architecture enabling the deployment of algorithms that must be solved in stringent times. That architecture can be based on a Path Computation Element (PCE) or a Software Defined Networks controller. In this thesis, we assume the former split in a front-end PCE, in charge of provisioning paths and handling network events, and a specialized planning tool in the form of a back-end PCE responsible for solving in-operation planning problems. After the architecture to support in-operation planning is assessed, we focus on studying the following applications: 1) Spectrum fragmentation is one of the most important problems in optical networks. To alleviate it to some extent without traffic disruption, we propose a hitless spectrum defragmentation strategy. 2) Each connection affected by a failure can be recovered using multiple paths to increase traffic restorability at the cost of poor resource utilization. We propose re-optimizing the network after repairing the failure to aggregate and reroute those connections to release spectral resources. 3) We study two approaches to provide multicast services: establishing a point-to-multipoint connections at the optical layer and using multi-purpose virtual network topologies (VNT) to serve both unicast and multicast connectivity requests. 4) The telecom cloud infrastructure, enables placing contents closer to the users. Based on it, we propose a hierarchical content distribution architecture where VNTs permanently interconnect core DCs and metro DCs periodically synchronize contents to the core DCs. 5) When the capacity of the optical backbone network becomes exhausted, we propose using a planning tool with access to inventory and operation databases to periodically decide the equipment and connectivity to be installed at the minimum cost reducing capacity overprovisioning. 6) In multi-domain multi-operator scenarios, a broker on top of the optical domains can provision multi-domain connections. We propose performing intra-domain spectrum defragmentation when no contiguous spectrum can be found for a new connection request. 7) Packet nodes belonging to a VNT can collect and send incoming traffic monitoring data to a big data repository. We propose using the collected data to predict next period traffic and to adapt the VNT to future conditions. The methodology followed in this thesis consists in proposing a problem statement and/or a mathematical formulation for the problems identified and then, devising algorithms for solving them. Those algorithms are simulated and then, they are experimentally assessed in real test-beds. This thesis demonstrates the feasibility of performing in-operation planning in optical networks, shows that it enhances the performance of the network and validates the feasibility of its deployment in real networks. It shall be mentioned that part of the work reported in this thesis has been done within the framework of several research projects, namely IDEALIST (FP7-ICT-2011-8) and GEANT (238875) funded by the EC and SYNERGY (TEC2014-59995-R) funded by the MINECO.

The ever increasing IP traffic volume has finally brought to light the high inefficiency of current wavelength-routed over rigid-grid optical networks in matching the client layer requirements. Such an issue results in the deployment of large-size, expensive and power-consuming Multiprotocol Label Switching (MPLS) layers to perform the required grooming/aggregation functionality. To deal with this problem, the emerging flexgrid technology, allowing for reduced size frequency grids, is being standardized. Flexgrid optical networks divide the spectrum into frequency slots providing finer granularity than rigid networks based on Dense Wavelength Division Multiplexing (DWDM). To find a feasible allocation, new Routing and Spectrum Allocation (RSA) algorithms for flexgrid optical networks need to be designed and evaluated. Furthermore, due to the flexibility of flexible optical networks, the aggregation functions and statistical multiplexing can be partially located in the optical layer. In addition, given the special characteristics of flexible optical networks, the traditional mechanisms for protection and recovery must be reformulated. Optical transport platforms are designed to facilitate the setting up and tearing down of optical connections (lightpaths). Combining remotely configurable optical cross-connects (OXCs) with a control plane provides the capability of automated lightpath set-up for regular provisioning, and real-time reaction to the failures, being thus able to reduce Operational Expenditures (OPEX). However, to exploit existing capacity, increase dynamicity, and provide automation in future networks, current management architectures, utilizing legacy Network Management Systems (NMS) need to be radically transformed. This thesis is devoted to design optical networks and to devise algorithms to operate them. Network design objective consists of: i.Analyzing the cost implications that a set of frequency slot widths have on the Capital Expenditures (CAPEX) investments required to deploy MPLS-over-flexgrid networks; ii.Studying recovery schemes, where a new recovery scheme specifically designed for flexgrid-based optical networks is proposed. As for network operation, we focus on: i.Studying provisioning, where two provisioning algorithms are proposed: the first one targets at solving the RSA problem in flexgrid networks, whereas the second one studies provisioning considering optical impairments in translucent DWDM networks; ii.Getting back to the recovery problem, we focus on algorithms to cope with restoration in dynamic scenarios. Several algorithms are proposed for both single layer and multilayer networks to be deployed in the centralized Path Computation Element (PCE); iii.One of the main problems in flexgrid networks is spectrum defragmentation. In view of that, we propose an algorithm to reallocate already established optical connections so as to make room for incoming requests. This algorithm is extended with elasticity to deal with time-varying traffic. The above algorithms are firstly implemented and validated by using simulation, and finally experimentally assessed in real test-beds. In view of PCE architectures do not facilitate network reconfiguration, we propose a control and management architecture to allow the network to be dynamically operated; network resources can be made available by reconfiguring and/or re-optimizing the network on demand and in real-time. We call that as in-operation network planning. It shall be mentioned that part of the work reported in this thesis has been done within the framework of several European and National projects, namely STRONGEST (FP7-247674), IDEALIST (FP7-ICT-2011-8), and GEANT (FP7-238875) funded by the European Commission, and ENGINE (TEC2008-02634) and ELASTIC (TEC2011-27310) funded by the Spanish Science Ministry.

Explains the importance of Elastic Optical Networks (EONs) and how they can be implemented by the world’s carriers This book discusses Elastic Optical Networks (EONs) from an operational perspective. It presents algorithms that are suitable for real-time operation and includes experimental results to further demonstrate the feasibility of the approaches discussed. It covers practical issues such as provisioning, protection, and defragmentation. It also presents provisioning and recovery in single layer elastic optical networks (EON). The authors review algorithms for provisioning point-to-point, anycast, and multicast connections, as well as transfer-based connections for datacenter interconnection. They also include algorithms for recovery connections from failures in the optical layer and in-operation planning algorithms for EONs. Provisioning, Recovery and In-operation Planning in Elastic Optical Network also examines multi-layer scenarios. It covers virtual network topology reconfiguration and multi-layer recovery, and includes provisioning customer virtual networks and the use of data analytics in order to bring cognition to the network. In addition, the book: Presents managing connections dynamically—and the flexibility to adapt the connection bitrate to the traffic needs fit well for new types of services, such as datacenter interconnection and Network Function Virtualization (NFV) Examines the topic in a holistic and comprehensive way, addressing control and management plane issues for provisioning, recovery, and in-operation planning Covers provisioning, recovery, and in-operation planning for EONs at the proposed exhaustive level The rapid expanse of new services has made the use of EONs (a relatively new concept) a necessity. That’s why this book is perfect for students and researchers in the field of technologies for optical networks (specifically EONs), including network architectures and planning, dynamic connection provisioning, on-line network re-optimization, and control and management planes. It is also an important text for engineers and practitioners working for telecom network operators, service providers, and vendors that require knowledge on a rapidly evolving topic.

Explains the importance of Elastic Optical Networks (EONs) and how they can be implemented by the world’s carriers This book discusses Elastic Optical Networks (EONs) from an operational perspective. It presents algorithms that are suitable for real-time operation and includes experimental results to further demonstrate the feasibility of the approaches discussed. It covers practical issues such as provisioning, protection, and defragmentation. It also presents provisioning and recovery in single layer elastic optical networks (EON). The authors review algorithms for provisioning point-to-point, anycast, and multicast connections, as well as transfer-based connections for datacenter interconnection. They also include algorithms for recovery connections from failures in the optical layer and in-operation planning algorithms for EONs. Provisioning, Recovery and In-operation Planning in Elastic Optical Network also examines multi-layer scenarios. It covers virtual network topology reconfiguration and multi-layer recovery, and includes provisioning customer virtual networks and the use of data analytics in order to bring cognition to the network. In addition, the book: Presents managing connections dynamically—and the flexibility to adapt the connection bitrate to the traffic needs fit well for new types of services, such as datacenter interconnection and Network Function Virtualization (NFV) Examines the topic in a holistic and comprehensive way, addressing control and management plane issues for provisioning, recovery, and in-operation planning Covers provisioning, recovery, and in-operation planning for EONs at the proposed exhaustive level The rapid expanse of new services has made the use of EONs (a relatively new concept) a necessity. That’s why this book is perfect for students and researchers in the field of technologies for optical networks (specifically EONs), including network architectures and planning, dynamic connection provisioning, on-line network re-optimization, and control and management planes. It is also an important text for engineers and practitioners working for telecom network operators, service providers, and vendors that require knowledge on a rapidly evolving topic.

The 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.

This book presents advances in the field of optical networks - specifically on research and applications in elastic optical networks (EON). The material reflects the authors’ extensive research and industrial activities and includes contributions from preeminent researchers and practitioners in optical networking. The authors discuss the new research and applications that address the issue of increased bandwidth demand due to disruptive, high bandwidth applications, e.g., video and cloud applications. The book also discusses issues with traffic not only increasing but becoming much more dynamic, both in time and direction, and posits immediate, medium, and long-term solutions throughout the text. The book is intended to provide a reference for network architecture and planning, communication systems, and control and management approaches that are expected to steer the evolution of EONs.

With the advent of Big Data, conventional communication networks are often limited in their inability to handle complex and voluminous data and information as far as effective processing, transmission, and reception are concerned. This book discusses the evolution of computational intelligence techniques in handling intelligent communication networks. Provides a detailed theoretical foundation of machine learning and computational intelligence algorithms Highlights the state of art machine learning-based solutions for communication networks Presents video demonstrations and code snippets on each chapter for easy understanding of the concepts Discusses applications including resource allocation, spectrum management, channel estimation, and physical layer of wireless networks Demonstrates applications of machine learning techniques for optical networks The text is primarily intended for senior undergraduate and graduate students and academic researchers in fields of electrical engineering, electronics and communication engineering, and computer engineering.