Mobility Models for Next Generation Wireless Networks

Mobility Models for Next Generation Wireless Networks: Ad Hoc, Vehicular and Mesh Networks provides the reader with an overview of mobility modelling, encompassing both theoretical and practical aspects related to the challenging mobility modelling task.

Auteur

Dr. Paolo Santi, Istituto di Informatica e Telematica del CNR, Italy
Dr. Santi received the Laura Degree and Ph.D. degree in computer science from the University of Pisa in 1994 and 2000, respectively. He is part of the research staff at the Istituto di Informatica e Telematica del CNR in Pisa, Italy, since 2001, first as a Researcher and now as a Senior Researcher.

During his career, he visited Georgia Institute of Technology in 2001 and Carnegie Mellon University in 2003. His research interests include fault-tolerant computing in multiprocessor systems (during PhD studies), and, more recently, the investigation of fundamental properties of wireless multihop networks such as connectivity, topology control, lifetime, capacity, mobility modelling, and cooperation issues.

Contenu

List of Figures xv List of Tables xxiii

About the Author xxv

Preface xxvii

Acknowledgments xxxiii

List of Abbreviations xxxv

Part I INTRODUCTION

1 Next Generation Wireless Networks 3

1.1 WLAN and Mesh Networks 5

1.2 Ad Hoc Networks 8

1.3 Vehicular Networks 10

1.4 Wireless Sensor Networks 13

1.5 Opportunistic Networks 14

2 Modeling Next Generation Wireless Networks 19

2.1 Radio Channel Models 20

2.2 The Communication Graph 26

2.3 The Energy Model 31

3 Mobility Models for Next Generation Wireless Networks 33

3.1 Motivation 33

3.2 Cellular vs. Next Generation Wireless Network Mobility Models 35

3.3 A Taxonomy of Existing Mobility Models 38

3.4 Mobility Models and Real-World Traces: The CRAWDAD Resource 43

3.5 Basic Definitions 45

Part II "GENERAL-PURPOSE" MOBILITY MODELS

4 Random Walk Models 51

4.1 Discrete Random Walks 52

4.2 Continuous Random Walks 55

4.3 Other Random Walk Models 57

4.4 Theoretical Properties of Random Walk Models 58

5 The Random Waypoint Model 61

5.1 The RWP Model 62

5.2 The Node Spatial Distribution of the RWP Model 64

5.3 The Average Nodal Speed of the RWP Model 69

5.4 Variants of the RWP Model 73

6 Group Mobility and Other Synthetic Mobility Models 75

6.1 The RPGM Model 76

6.2 Other Synthetic Mobility Models 83

7 Random Trip Models 89

7.1 The Class of Random Trip Models 89

7.2 Stationarity of Random Trip Models 93

7.3 Examples of Random Trip Models 94

Part III MOBILITY MODELS FOR WLAN AND MESH NETWORKS

8 WLAN and Mesh Networks 101

8.1 WLAN and Mesh Networks: State of the Art 101

8.2 WLAN and Mesh Networks: User Scenarios 107

8.3 WLAN and Mesh Networks: Perspectives 109

8.4 Further Reading 111

9 Real-World WLAN Mobility 113

9.1 Real-World WLAN Traces 113

9.2 Features of WLAN Mobility 116

10 WLAN Mobility Models 121

10.1 The LH Mobility Model 122

10.2 The KKK Mobility Model 129

10.3 Final Considerations and Further Reading 137

Part IV MOBILITY MODELS FOR VEHICULAR NETWORKS

11 Vehicular Networks 141

11.1 Vehicular Networks: State of the Art 141

11.2 Vehicular Networks: User Scenarios 146

11.3 Vehicular Networks: Perspectives 150

11.4 Further Reading 151

12 Vehicular Networks: Macroscopic and Microscopic Mobility Models 153

12.1 Vehicular Mobility Models: The Macroscopic View 154

12.2 Vehicular Mobility Models: The Microscopic View 156

12.3 Further Reading 157

13 Microscopic Vehicular Mobility Models 159

13.1 Simple Microscopic Mobility Models 159

13.2 The SUMO Mobility Model 164

13.3 Integrating Vehicular Mobility and Wireless Network Simulation 168

Part V MOBILITY MODELS FOR WIRELESS SENSOR NETWORKS

14 Wireless Sensor Networks 175

14.1 Wireless Sensor Networks: State of the Art 175

14.2 Wireless Sensor Networks: User Scenarios 180

14.3 WSNs: Perspectives 183

14.4 Further Reading 184

15 Wireless Sensor Networks: Passive Mobility Models 185

15.1 Passive Mobility in WSNs 186

15.2 Mobility Models for Wildlife Tracking Applications 187

15.3 Modeling Movement Caused by External Forces 191

16 Wireless Sensor Networks: Active Mobility Models 197

16.1 Active Mobility of Sensor Nodes 198

16.2 Active Mobility of Sink Nodes 208

Part VI MOBILITY MODELS FOR OPPORTUNISTIC NETWORKS

17 Opportunistic Networks 217

17.1 Opportunistic Networks: State of the Art 217

17.2 Opportunistic Networks: User Scenarios 219

17.3 Opportunistic Networks: Perspectives 222

17.4 Further Reading 223

18 Routing in Opportunistic Networks 225

18.1 Mobility-Assisted Routing in Opportunistic Networks 225

18.2 Opportunistic Network Mobility Metrics 231

19 Mobile Social Network Analysis 237

19.1 The Social Network Graph 238

19.2 Centrality and Clustering Metrics 239

19.3 Characterizations of Human Mobility 244

19.4 Further Reading 250

20 Social-Based Mobility Models 251

20.1 The Weighted Random Waypoint Mobility Model 252

20.2 The Time-Variant Community Mobility Model 254

20.3 The Community-Based Mobility Model 256

20.4 The SWIM Mobility Model 259

20.5 The Self-Similar Least Action Walk Model 264

20.6 The Home-MEG Model 267

20.7 Further Reading 270

Part VII CASE STUDIES

21 Random Waypoint Model and Wireless Network Simulation 275

21.1 RWP Model and Simulation Accuracy 276

21.2 Removing the Border Effect 278

21.3 Removing Speed Decay 285

21.4 The RWP Model and "Perfect Simulation" 287

22 Mobility Modeling and Opportunistic Network Performance Analysis 293

22.1 Unicast in Opportunistic Networks 293

22.2 Broadcast in Opportunistic Networks 299

Appendix A Elements of Probability Theory 309

A.1 Basic Notions of Probability Theory 309

A.2 Probability Distributions 313

A.3 Markov Chains 317

Appendix B Elements of Graph Theory, Asymptotic Notation, and Miscellaneous Notions 323

B.1 Asymptotic Notation 323

B.2 Elements of Graph Theory 326

B.3 Miscellaneous Notions 330

References 333

Index 335