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.

Table of Contents:
List of Contributors xiii 1 Motivation 1 1.1 Motivation 1 1.2 Book Outline 8 1.3 Book Itineraries 11 Acknowledgment 12 Part I Introduction 13 2 Background 15 2.1 Introduction to Graph Theory 16 2.2 Introduction to Optimization 20 2.3 ILP Models and Heuristics for Routing Problems 22 2.3.1 ILP Formulations 22 2.3.2 Heuristics 25 2.3.3 Meta]Heuristics 27 2.4 Introduction to the Optical Technology 30 2.4.1 From Opaque to Transparent Optical Networks 31 2.4.2 Single]Layer and Multilayer Networks 32 2.4.3 EON Key Technologies 33 2.5 Network Life Cycle 35 2.5.1 Connection Provisioning 36 2.5.2 Connection Recovery 37 2.6 Conclusions 40 3 The Routing and Spectrum Allocation Problem 43 3.1 Introduction 44 3.2 The RSA Problem 45 3.2.1 Basic Offline Problem Statement 45 3.2.2 Notation 46 3.3 ILP Formulations Based On Slice Assignment 47 3.3.1 Starting Slice Assignment RSA (SSA]RSA) Formulation 47 3.3.2 Slice Assignment RSA (SA]RSA) Formulation 48 3.4 ILP Formulations Based On Slot Assignment 49 3.4.1 Slot Precomputation 49 3.4.2 Slot Assignment RSA (CA]RSA) Formulation 50 3.5 Evaluation of the ILP Formulations 51 3.5.1 Model Size Analysis 51 3.5.2 Performance Comparison 52 3.5.3 Evaluation in Real Scenarios 54 3.6 The RMSA Problem 56 3.6.1 Notation Extensions 56 3.6.2 Basic Offline Problem 56 3.6.3 Topology Design Problem as an RMSA Problem 57 3.7 Conclusions 60 4 Architectures for Provisioning and In]operation Planning 61 4.1 Introduction 62 4.2 Architectures for Dynamic Network Operation 64 4.2.1 Static versus Dynamic Network Operation 64 4.2.2 Migration toward In]operation Network Planning 65 4.2.3 Required Functionalities 67 4.2.4 The Front]end/Back]end PCE Architecture 68 4.3 In]operation Planning: Use Cases 73 4.3.1 VNT Reconfiguration after a Failure 73 4.3.2 Reoptimization 76 4.4 Toward Cloud]Ready Transport Networks 78 4.5 Conclusions 84 Part II Provisioning in Single Layer Networks 85 5 Dynamic Provisioning of p2p Demands 87 5.1 Introduction 88 5.2 Provisioning in Transparent Networks 90 5.2.1 Problem Statement 90 5.2.2 Dynamic RSA Algorithm 90 5.2.3 Dynamic RMSA Algorithm 91 5.2.4 Bulk RSA Algorithm 92 5.2.5 Illustrative Results 93 5.3 Provisioning in Translucent Networks 99 5.4 Dynamic Spectrum Allocation Adaption 102 5.4.1 Spectrum Allocation Policies 103 5.4.2 Problem Statement 104 5.4.3 Spectrum Adaption Algorithms 105 5.4.4 Illustrative Results 106 5.5 Conclusions 110 6 Transfer]based Datacenter Interconnection 113 6.1 Introduction 114 6.2 Application Service Orchestrator 116 6.2.1 Models for Transfer]based Connections 117 6.2.2 Illustrative Results 121 6.3 Routing and Scheduled Spectrum Allocation 124 6.3.1 Managing Transfer]based Connections 124 6.3.2 The RSSA Problem 126 6.3.3 ILP Formulation 127 6.3.4 Algorithms to Manage Transfer]based Requests 130 6.3.5 Illustrative Results 132 6.4 Conclusions 138 7 Provisioning Multicast and Anycast Demands 141 7.1 Introduction 142 7.2 Multicast Provisioning 143 7.2.1 P2MP]RSA Problem Statement 145 7.2.2 ILP Formulation 145 7.2.3 Heuristic Algorithm 148 7.2.4 Illustrative Numerical Results 150 7.2.5 Proposed Workflows and Protocol Issues 152 7.2.6 Experimental Assessment 154 7.3 Anycast Provisioning 156 7.3.1 Optical Anycast (AC_RSA) Problem Statement 157 7.3.2 Exact Algorithm for the AC_RSA Problem 157 7.3.3 Illustrative Numerical Results 158 7.3.4 Proposed Workflow 159 7.3.5 Experimental Assessment 161 7.4 Conclusions 162 Part III Recovery and In]operation Planning in Single Layer Networks 163 8 Spectrum Defragmentation 165 8.1 Introduction 166 8.2 Spectrum Reallocation and Spectrum Shifting 168 8.3 Spectrum Reallocation: The SPRESSO Problem 170 8.3.1 Problem Statement 170 8.3.2 ILP Formulation 170 8.3.3 Heuristic Algorithm 172 8.4 Spectrum Shifting: The SPRING Problem 178 8.4.1 Problem Statement 178 8.4.2 ILP Formulation 178 8.4.3 Heuristic Algorithm 179 8.5 Performance Evaluation 180 8.5.1 SPRESSO Heuristics Tuning 180 8.5.2 Heuristics versus the ILP Model 182 8.5.3 Performance of the SPRESSO Algorithm 182 8.6 Experimental Assessment 184 8.6.1 Proposed Workflow and Algorithm 184 8.6.2 PCEP Issues 186 8.6.3 Experiments 188 8.7 Conclusions 191 9 Restoration in the Optical Layer 193 9.1 Introduction 194 9.2 Bitrate Squeezing and Multipath Restoration 195 9.2.1 The BATIDO Problem 197 9.2.2 ILP Formulation 197 9.2.3 Heuristic Algorithm 200 9.2.4 Numerical Results 202 9.3 Modulation Format]Aware Restoration 207 9.3.1 The MF]Restoration Problem 210 9.3.2 Algorithm for MF]Restoration 211 9.3.3 Protocol Extensions and Proposed Workflows 213 9.3.4 Experimental Assessment 216 9.4 Recovering Anycast Connections 216 9.4.1 ILP Formulations and Algorithm 217 9.4.2 Proposed Workflow 220 9.4.3 Validation 221 9.5 Conclusions 223 10 After]Failure]Repair Optimization 225 10.1 Introduction 226 10.2 The AFRO Problem 228 10.2.1 Problem Statement 230 10.2.2 Optimization Algorithm 230 10.2.3 ILP Formulation 231 10.2.4 Heuristic Algorithm 233 10.2.5 Disruption Considerations 234 10.2.6 Performance Evaluation 236 10.3 Restoration and AFRO with Multiple Paths 240 10.3.1 Problem Statement 242 10.3.2 MILP Formulation 242 10.3.3 Heuristic Algorithm 244 10.3.4 MP]AFRO Performance Evaluation 245 10.4 Experimental Validation 246 10.4.1 Proposed Reoptimization Workflow 246 10.4.2 Experimental Assessment 249 10.5 Conclusions 252 Part IV Multilayer Networks 255 11 Virtual Network Topology Design and Reconfiguration 257 11.1 Introduction 258 11.2 VNT Design and Reconfiguration Options 259 11.3 Static VNT Design 262 11.3.1 The VNT Design Problem 262 11.3.2 MILP Formulation 262 11.4 VNT Reconfiguration Based on Traffic Measures 264 11.4.1 The VENTURE Problem 264 11.4.2 ILP Formulation 265 11.4.3 Heuristic Algorithm 267 11.4.4 Proposed Workflow 272 11.5 Results 273 11.5.1 Simulation Results 273 11.5.2 Experimental Assessment 275 11.6 Conclusions 278 12 Recovery in Multilayer Networks 279 12.1 Introduction 280 12.2 Path Restoration in GMPLS]Controlled Networks 281 12.2.1 The DYNAMO Problem 285 12.2.2 MP Formulation 285 12.2.3 Heuristic Algorithm 290 12.2.4 DYNAMO Numerical Results 290 12.2.5 PCE Architecture 297 12.2.6 Experimental Results 299 12.3 Survivable VNT for DC Synchronization 302 12.3.1 Mathematical Formulations and Algorithms 304 12.3.2 Workflows and Protocol Extensions 309 12.3.3 Experimental Assessment 310 12.4 Conclusions 312 Part V Future Trends 313 13 High Capacity Optical Networks Based on Space Division Multiplexing 315 13.1 Introduction 316 13.2 SDM Fibers 319 13.2.1 Uncoupled/Weakly Coupled Spatial Dimensions 320 13.2.2 Strongly Coupled Spatial Dimensions 320 13.2.3 Subgroups of Strongly Coupled Spatial Dimensions 321 13.3 SDM Switching Paradigms 322 13.4 Resource Allocation in SDM Networks 325 13.5 Impact of Traffic Profile on the Performance of Spatial Sp]Ch Switching in SDM Networks 332 13.5.1 Illustrative Results 333 13.6 Impact of Spatial and Spectral Granularity on the Performance of SDM Networks Based on Spatial Sp]Ch Switching 336 13.6.1 Illustrative Results 338 13.7 Conclusions 342 14 Dynamic Connectivity Services in Support of Future Mobile Networks 345 14.1 Introduction 346 14.2 C]RAN Requirements and CVN Support 348 14.2.1 C]RAN Architecture Model 349 14.2.2 Backhaul Requirements in C]RAN 349 14.2.3 CVN Reconfiguration 351 14.3 The CUVINET Problem 354 14.3.1 Problem Statement 354 14.3.2 MILP Formulation 355 14.3.3 Heuristic Algorithm 359 14.4 Illustrative Numerical Results 361 14.4.1 Network Scenario 361 14.4.2 Heuristic Algorithm Validation 362 14.4.3 Approaches to Support CVNs 362 14.4.4 Performance Evaluation 363 14.5 Conclusions 367 15 Toward Cognitive In]operation Planning 369 15.1 Introduction 370 15.2 Data Analytics for Failure Localization 371 15.2.1 Algorithm for Failure Identification/Localization 372 15.2.2 Experiments and Results 375 15.2.3 Generic Modules to Implement the OAA Loop 377 15.3 Data Analytics to Model Origin–Destination Traffic 378 15.3.1 Generic Modules for VNT Reconfiguration Based on Traffic Modeling 378 15.3.2 Machine Learning Procedure for Traffic Estimation 380 15.3.3 Use Case I: Anomaly Detection 383 15.3.4 Use Case II: VNT Reconfiguration Triggered by Anomaly Detection 390 15.4 Adding Cognition to the ABNO Architecture 393 15.5 Conclusions 395 List of Acronyms 397 References 403 Index 419