Atjaunināt sīkdatņu piekrišanu

E-grāmata: Mobility Models for Next Generation Wireless Networks - Ad Hoc, Vehicular and Mesh Networks: Ad Hoc, Vehicular and Mesh Networks [Wiley Online]

(Istituto di Informatica e Telematica del CNR, Italy)
Citas grāmatas par šo tēmu:
  • Wiley Online
  • Cena: 135,46 €*
  • * this price gives unlimited concurrent access for unlimited time
Mobility Models for Next Generation Wireless Networks - Ad Hoc, Vehicular and Mesh Networks: Ad Hoc, Vehicular and Mesh NetworksPalielināt
Citas grāmatas par šo tēmu:
Wiley Online E-booksMore info about Wiley Online
Rokasgrāmatas mājas lapa: https://onlinelibrary.wiley.com/doi/book/10.1002/9781118344774

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
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(16)
1.1 WLAN and Mesh Networks
5(3)
1.2 Ad Hoc Networks
8(2)
1.3 Vehicular Networks
10(3)
1.4 Wireless Sensor Networks
13(1)
1.5 Opportunistic Networks
14(5)
References
16(3)
2 Modeling Next Generation Wireless Networks
19(14)
2.1 Radio Channel Models
20(6)
2.2 The Communication Graph
26(5)
2.3 The Energy Model
31(2)
References
32(1)
3 Mobility Models for Next Generation Wireless Networks
33(18)
3.1 Motivation
33(2)
3.2 Cellular vs. Next Generation Wireless Network Mobility Models
35(3)
3.3 A Taxonomy of Existing Mobility Models
38(5)
3.3.1 Spatial Scope
39(1)
3.3.2 Application Scenario
40(1)
3.3.3 Nature
41(1)
3.3.4 Correlation
41(1)
3.3.5 Geography
42(1)
3.3.6 Trajectory
42(1)
3.4 Mobility Models and Real-World Traces: The CRAWDAD Resource
43(2)
3.5 Basic Definitions
45(6)
References
47(4)
Part II "GENERAL-PURPOSE" MOBILITY MODELS
4 Random Walk Models
51(10)
4.1 Discrete Random Walks
52(3)
4.1.1 Random Walks on Grids
53(1)
4.1.2 Random Walks on Graphs
54(1)
4.2 Continuous Random Walks
55(2)
4.2.1 Brownian Motion
55(1)
4.2.2 Levy flight
56(1)
4.3 Other Random Walk Models
57(1)
4.4 Theoretical Properties of Random Walk Models
58(3)
4.4.1 Stationary Node Spatial Distribution
58(1)
4.4.2 The Level-Crossing Phenomenon
59(1)
4.4.3 Hitting Time, Return Time, and Cover Time
60(1)
References
60(1)
5 The Random Waypoint Model
61(14)
5.1 The RWP Model
62(2)
5.2 The Node Spatial Distribution of the RWP Model
64(5)
5.3 The Average Nodal Speed of the RWP Model
69(4)
5.4 Variants of the RWP Model
73(2)
References
74(1)
6 Group Mobility and Other Synthetic Mobility Models
75(14)
6.1 The RPGM Model
76(7)
6.1.1 RPGM with RWP Group Mobility
79(1)
6.1.2 In-Place Mobility Model
79(1)
6.1.3 Convention Mobility Model
80(2)
6.1.4 RPGM and Other Group Mobility Models
82(1)
6.2 Other Synthetic Mobility Models
83(6)
6.2.1 The Smooth Random Mobility Model
83(3)
6.2.2 Gauss-Markov Mobility Model
86(1)
References
87(2)
7 Random Trip Models
89(12)
7.1 The Class of Random Trip Models
89(4)
7.1.1 Conditions on Phase and Path
91(1)
7.1.2 Conditions on Trip Duration
92(1)
7.2 Stationarity of Random Trip Models
93(1)
7.3 Examples of Random Trip Models
94(7)
7.3.1 Random Way point Model
94(2)
7.3.2 RWP Variants
96(1)
7.3.3 Other Random Trip Mobility Models
97(1)
References
98(3)
Part III MOBILITY MODELS FOR WLAN AND MESH NETWORKS
8 WLAN and Mesh Networks
101(12)
8.1 WLAN and Mesh Networks: State of the Art
101(6)
8.1.1 Network Architecture
102(2)
8.1.2 The IEEE 802.11 Standard
104(3)
8.2 WLAN and Mesh Networks: User Scenarios
107(2)
8.2.1 Home WLAN
107(1)
8.2.2 Campus/Corporate WLAN
107(1)
8.2.3 Public Area Hotspots
108(1)
8.2.4 Community Mesh Network
109(1)
8.3 WLAN and Mesh Networks: Perspectives
109(2)
8.4 Further Reading
111(2)
References
111(2)
9 Real-World WLAN Mobility
113(8)
9.1 Real-World WLAN Traces
113(3)
9.2 Features of WLAN Mobility
116(5)
References
119(2)
10 WLAN Mobility Models
121(20)
10.1 The LH Mobility Model
122(7)
10.1.1 Estimating the Transition and Steady-State Probabilities
123(1)
10.1.2 Finding Temporal Correlation in User/AP Association Patterns
124(3)
10.1.3 Timed Location Prediction with the LH Model
127(2)
10.2 The KKK Mobility Model
129(8)
10.2.1 Extracting Physical Movement Trajectories from WLAN Traces
129(3)
10.2.2 Extracting Pause Time
132(1)
10.2.3 Dealing with Stationary Sub-Traces
133(1)
10.2.4 Finding Hotspot Locations
133(2)
10.2.5 Mobility Modeling
135(2)
10.3 Final Considerations and Further Reading
137(4)
References
138(3)
Part IV MOBILITY MODELS FOR VEHICULAR NETWORKS
11 Vehicular Networks
141(12)
11.1 Vehicular Networks: State of the Art
141(5)
11.1.1 Motivation
143(1)
11.1.2 Standardization Activities
144(2)
11.2 Vehicular Networks: User Scenarios
146(4)
11.2.1 Active Safety Applications
147(2)
11.2.2 Cooperative Traffic Efficiency Applications
149(1)
11.2.3 Cooperative Local Services
150(1)
11.2.4 Global Internet Services
150(1)
11.3 Vehicular Networks: Perspectives
150(1)
11.4 Further Reading
151(2)
References
152(1)
12 Vehicular Networks: Macroscopic and Microscopic Mobility Models
153(6)
12.1 Vehicular Mobility Models: The Macroscopic View
154(2)
12.2 Vehicular Mobility Models: The Microscopic View
156(1)
12.3 Further Reading
157(2)
References
158(1)
13 Microscopic Vehicular Mobility Models
159(16)
13.1 Simple Microscopic Mobility Models
159(5)
13.1.1 The Graph-Based Mobility Model
159(1)
13.1.2 The Freeway Mobility Model
160(3)
13.1.3 The Manhattan Mobility Model
163(1)
13.2 The SUMO Mobility Model
164(4)
13.2.1 Building the Road Network
166(1)
13.2.2 Building the Traffic Demand
167(1)
13.2.3 Route Computation
167(1)
13.2.4 Running the Simulation and Generating Output
168(1)
13.3 Integrating Vehicular Mobility and Wireless Network Simulation
168(7)
13.3.1 The TraCI Interface for Coupled Vehicular Network Simulation
170(2)
References
172(3)
Part V MOBILITY MODELS FOR WIRELESS SENSOR NETWORKS
14 Wireless Sensor Networks
175(10)
14.1 Wireless Sensor Networks: State of the Art
175(5)
14.1.1 Hardware and Software Platforms
177
14.1.2 Standardization Activities
111(69)
14.2 Wireless Sensor Networks: User Scenarios
180(3)
14.2.1 Environmental Monitoring
180(1)
14.2.2 Industrial Monitoring
181(1)
14.2.3 Health and Well-Being Monitoring
181(1)
14.2.4 Precision Agriculture
181(1)
14.2.5 Seismic, Structural, and Building Monitoring
182(1)
14.2.6 Intrusion Detection
182(1)
14.2.7 Tracking of Objects, People, and Animals
183(1)
14.3 WSNs: Perspectives
183(1)
14.4 Further Reading
184(1)
References
184(1)
15 Wireless Sensor Networks: Passive Mobility Models
185(12)
15.1 Passive Mobility in WSNs
186(1)
15.2 Mobility Models for Wildlife Tracking Applications
187(4)
15.2.1 The ZebraNet Mobility Model
187(3)
15.2.2 The Whale Mobility Model
190(1)
15.3 Modeling Movement Caused by External Forces
191(6)
References
194(3)
16 Wireless Sensor Networks: Active Mobility Models
197(20)
16.1 Active Mobility of Sensor Nodes
198(10)
16.1.1 Active Mobility and Sensing Coverage
198(3)
16.1.2 Motion Control for Sensing Coverage
201(5)
16.1.3 Motion Control for Event Tracking
206(2)
16.2 Active Mobility of Sink Nodes
208(9)
16.2.1 The Data MULE Concept
209(1)
16.2.2 Sink Mobility for Network Lifetime Maximization
210(2)
References
212(5)
Part VI MOBILITY MODELS FOR OPPORTUNISTIC NETWORKS
17 Opportunistic Networks
217(8)
17.1 Opportunistic Networks: State of the Art
217(2)
17.2 Opportunistic Networks: User Scenarios
219(3)
17.2.1 User Scenarios in PSNs
220(1)
17.2.2 User Scenarios in WSNs
221(1)
17.2.3 User Scenarios in Vehicular Networks
221(1)
17.3 Opportunistic Networks: Perspectives
222(1)
17.4 Further Reading
223(2)
References
223(2)
18 Routing in Opportunistic Networks
225(12)
18.1 Mobility-Assisted Routing in Opportunistic Networks
225(6)
18.1.1 Single-Copy Protocols
227(2)
18.1.2 Multi-Copy Protocols
229(2)
18.2 Opportunistic Network Mobility Metrics
231(6)
18.2.1 The Expected Meeting Time
231(1)
18.2.2 The Inter-Meeting Time
232(1)
18.2.3 Contact Duration
233(1)
18.2.4 Relating the Three Metrics
234(1)
References
235(2)
19 Mobile Social Network Analysis
237(14)
19.1 The Social Network Graph
238(1)
19.2 Centrality and Clustering Metrics
239(5)
19.2.1 Centrality Metrics
240(2)
19.2.2 Clustering Metrics
242(2)
19.3 Characterizations of Human Mobility
244(6)
19.3.1 Characterization of Individual Human Mobility Patterns
245(2)
19.3.2 Characterization of Pairwise Contact Patterns
247(3)
19.4 Further Reading
250(1)
References
250(1)
20 Social-Based Mobility Models
251(24)
20.1 The Weighted Random Waypoint Mobility Model
252(2)
20.2 The Time-Variant Community Mobility Model
254(2)
20.3 The Community-Based Mobility Model
256(3)
20.4 The SWIM Mobility Model
259(5)
20.5 The Self-Similar Least Action Walk Model
264(3)
20.6 The Home-MEG Model
267(3)
20.7 Further Reading
270(5)
References
271(4)
Part VII CASE STUDIES
21 Random Waypoint Model and Wireless Network Simulation
275(18)
21.1 RWP Model and Simulation Accuracy
276(2)
21.2 Removing the Border Effect
278(7)
21.2.1 The Temporal-RWP Model
279(2)
21.2.2 The Spatial-RWP Model
281(4)
21.3 Removing Speed Decay
285(2)
21.4 The RWP Model and "Perfect Simulation"
287(6)
References
290(3)
22 Mobility Modeling and Opportunistic Network Performance Analysis
293(16)
22.1 Unicast in Opportunistic Networks
293(6)
22.7.7 Network Model
294(3)
22.7.2 Epidemic Routing Performance
297(1)
22.1.3 Two-Hops Routing Performance
298(1)
22.2 Broadcast in Opportunistic Networks
299(10)
22.2.7 Network Model
300(2)
22.2.2 Broadcasting with Geometric-Based Mobility
302(1)
22.2.3 Broadcasting with the Home-MEG Model
303(3)
22.2.4 Discussion
306(2)
References
308(1)
Appendix A Elements of Probability Theory
309(14)
A.1 Basic Notions of Probability Theory
309(4)
A.2 Probability Distributions
313(4)
A.3 Markov Chains
317(6)
References
321(2)
Appendix B Elements of Graph Theory, Asymptotic Notation, and Miscellaneous Notions
323(12)
B.1 Asymptotic Notation
323(3)
B.2 Elements of Graph Theory
326(4)
B.3 Miscellaneous Notions
330(5)
References
333(2)
Index 335
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.
Permanent link: https://www.kriso.lv/db/9781118344774_pe.html
Keywords: