Provisioning, Recovery, and in-operation Planning in Elastic Optical Networks

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.

LUIS VELASCO, PhD, is a full Professor at Universitat Politecnica de Catalunya, BarcelonaTech, Spain. He has devoted more than 25 years in the telecommunications industry for advanced research, development, and deployment of optical networks.

MARC RUIZ, PhD, is an associate researcher at Universitat Politècnica de Catalunya, BarcelonaTech, Spain, and is highly skilled in operations research and statistics applied to communication networks.

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

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