Mobility Models for Next Generation Wireless Networks: Ad Hoc, Vehicular and Mesh Networks(Wiley Series on Communications Networking & Distributed Systems)

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. It also: Provides up-to-date coverage of mobility models for next generation wireless networks Offers an in-depth discussion of the most representative mobility models for major next generation wireless network application scenarios, including WLAN/mesh networks, vehicular networks, wireless sensor networks, and opportunistic networks Demonstrates the practices for designing effective protocol/applications for next generation wireless networks Includes case studies showcasing the importance of properly understanding fundamental mobility model properties in wireless network performance evaluation

Table of Contents:
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

About the Author :
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.