Atnaujinkite slapukų nuostatas

El. knyga: Wireless Sensor Networks: Principles and Practice [Taylor & Francis e-book]

(Georgia State University, Atlanta, Georgia, USA), (University of Alabama, Tuscaloosa, USA)
  • Formatas: 532 pages, 21 Tables, black and white; 194 Illustrations, black and white
  • Išleidimo metai: 06-May-2010
  • Leidėjas: Auerbach
  • ISBN-13: 9780429111488
Kitos knygos pagal šią temą:
  • Taylor & Francis e-book
  • Kaina: 147,72 €*
  • * this price gives unlimited concurrent access for unlimited time
  • Standartinė kaina: 211,02 €
  • Sutaupote 30%
Wireless Sensor Networks: Principles and PracticeDidesnis paveikslėlis
  • Formatas: 532 pages, 21 Tables, black and white; 194 Illustrations, black and white
  • Išleidimo metai: 06-May-2010
  • Leidėjas: Auerbach
  • ISBN-13: 9780429111488
Kitos knygos pagal šią temą:
Taylor & Francis e-booksMore info about Taylor & Francis e-books
Partnerių interneto svetainė: https://www.taylorfrancis.com/books/9780429111488
Written by award-winning engineers whose research has been sponsored by the U.S. National Science Foundation (NSF), IBM, and Cisco's University Research Program, Wireless Sensor Networks: Principles and Practice addresses everything product developers and technicians need to know to navigate the field. It provides an all-inclusive examination of the major wireless sensor network (WSN) technology, standards, and application topics.

Using straightforward language, the text makes complex concepts and processes easy to understand. It covers hardware design, medium access control, routing schemes, transport protocols, OS support, middleware, data management, localization, synchronization, security, actuator/underwater/video sensor networking, power control, sensor simulations, and emerging research. This authoritative resource includes a wealth of exercises, end-of-chapter reviews, detailed case studies, as well as practical sensor network design cases that touch on medical applications.

Complete with class labs that illustrate how to apply concepts to the development and application of WSNs, this book spells out the steps of design and implementation needed to address real-world challenges and optimization problems. A CD with instructional resources, including solutions to exercises and lab materials, is available upon qualified course adoption.
Preface xvii
Acknowledgments xxiii
Disclaimer xxv
Authors xxvii
PART I BASICS
1 Introduction
3(24)
1.1 Basics
3(6)
1.2 MAC Layer
9(1)
1.3 Routing
10(1)
1.4 Other Communication Issues
10(2)
1.5 Sensor Localization
12(1)
1.6 Clock Synchronization
13(1)
1.7 Power Management
13(1)
1.8 Special WSNs
14(4)
1.8.1 Wireless Multimedia Sensor Networks
14(2)
1.8.2 Underwater Acoustic Sensor Networks
16(2)
1.9 WSN Applications
18(4)
Problems and Exercises
22(5)
PART II ENGINEERING DESIGN
2 Hardware—Sensor Mote Architecture and Design
27(40)
2.1 Components of a Sensor Mote
27(17)
2.1.1 Sensors
28(2)
2.1.2 Microprocessor
30(5)
2.1.3 Memory
35(1)
2.1.4 Radios
36(5)
2.1.5 Power Sources
41(2)
2.1.6 Peripheral Support
43(1)
2.2 Put Everything Together
44(4)
2.2.1 Typical Sensor Mote Architecture
44(8)
2.2.1.1 Wireless Communication Requirements
44(1)
2.2.1.2 Key Issues
45(1)
2.2.1.3 Traditional Wireless Design
46(1)
2.2.1.4 Mote Example: Reno
47(1)
2.3 Mica Mote Design
48(2)
2.4 Customized Mote—Spec
50(2)
2.5 COTS Dust Systems
52(2)
2.5.1 Design Advice: Failures and Successes
53(1)
2.6 Telos Mote
54(3)
2.7 CargoNet
57(5)
Problems and Exercises
62(5)
PART III NETWORK PROTOCOL STACK
3 Medium Access Control in Wireless Sensor Networks
67(42)
3.1 Introduction
67(5)
3.1.1 Medium Access Control in Wireless Networks
68(1)
3.1.2 MAC Design Is Challenging in WSNs
68(4)
3.1.2.1 Resource Constraints
68(1)
3.1.2.2 Signal Loss in Wireless Channel
69(1)
3.1.2.3 Collisions Occurring at the Receiver's End
70(1)
3.1.2.4 Hidden Terminal and Exposed Terminal Problems
70(2)
3.2 Overview of Project IEEE 802.11
72(5)
3.2.1 Point Coordination Function
73(1)
3.2.2 Distributed Coordination Function
74(3)
3.3 Classification of MAC Protocols
77(30)
3.3.1 Contention-Based MAC Protocols
77(11)
3.3.1.1 Sensor Medium Access Control
78(5)
3.3.1.2 Timeout MAC
83(5)
3.3.2 Schedule-Based MAC Protocols
88(6)
3.3.2.1 Traffic Adaptive Medium Access Protocol
89(5)
3.3.3 Hybrid and Event-Based MAC Protocols
94(15)
3.3.3.1 Sift Medium Access Control
94(6)
3.3.3.2 Berkeley Medium Access Control
100(2)
3.3.3.3 Zebra Medium Access Control
102(5)
3.4 Conclusion
107(1)
Problems and Exercises
107(2)
4 Routing in Wireless Sensor Networks
109(42)
4.1 Introduction
109(3)
4.1.1 Limited Resources in WSNs
110(1)
4.1.2 Fault Tolerance
110(1)
4.1.3 Data Reporting and Aggregation
111(1)
4.1.4 Node Deployment
111(1)
4.1.5 Scalability and Coverage
111(1)
4.1.6 Network Dynamics and Heterogeneity
112(1)
4.2 Layout for the
Chapter
112(1)
4.3 Classification of Routing Protocols in WSNs
113(1)
4.3.1 Proactive and Reactive Routing
113(1)
4.3.2 Flat and Hierarchical Routing
113(1)
4.4 Data-Centric Routing Protocols in WSNs
114(14)
4.4.1 Flooding and Gossiping
115(2)
4.4.1.1 Ideal Dissemination
117(1)
4.4.2 Sensor Protocols for Information via Negotiation
117(5)
4.4.2.1 Design of SPIN
118(1)
4.4.2.2 Different Types of SPIN
119(1)
4.4.2.3 Evaluating SPIN Protocols
120(2)
4.4.3 Directed Diffusion
122(6)
4.4.3.1 Naming
123(1)
4.4.3.2 Interest Propagation and Gradient Establishment
123(2)
4.4.3.3 Data Propagation
125(1)
4.4.3.4 Reinforcement
126(1)
4.4.3.5 Evaluating Directed Diffusion
127(1)
4.5 Hierarchical Routing Protocols in WSNs
128(10)
4.5.1 Low-Energy Adaptive Clustering Hierarchy Protocol
129(5)
4.5.1.1 Protocol Design
130(1)
4.5.1.2 Setup Phase: Cluster Formation and Cluster-Head Selection
130(1)
4.5.1.3 Steady State Phase
131(2)
4.5.1.4 LEACH-Centralized
133(1)
4.5.1.5 Evaluating LEACH Protocol
133(1)
4.5.2 Threshold-Sensitive Energy-Efficient Sensor Network Protocol
134(4)
4.5.2.1 Sensor Network Model in TEEN
134(1)
4.5.2.2 Operation of TEEN Protocol
134(2)
4.5.2.3 Evaluating TEEN Protocol
136(1)
4.5.2.4 Adaptive Periodic Threshold-Sensitive Energy-Efficient Network Protocol
137(1)
4.6 Location-Based Routing Protocols in WSNs
138(7)
4.6.1 Geographical and Energy-Aware Routing Protocol
139(6)
4.6.1.1 Phases of GEAR
139(1)
4.6.1.2 Energy-Aware Neighbor Computation
140(3)
4.6.1.3 Recursive Geographic Forwarding
143(1)
4.6.1.4 Evaluating GEAR Protocol
144(1)
4.7 Multipath and QoS-Based Routing
145(3)
4.7.1 Multipath Routing
145(2)
4.7.2 QoS-Based Routing Protocols in WSNs
147(1)
4.8 Conclusion
148(1)
Problems and Exercises
148(3)
5 Transport Layer in Wireless Sensor Networks
151(50)
5.1 Introduction
152(1)
5.2 Pump Slowly, Fetch Quickly
152(11)
5.2.1 Why Does TCP Not Work Well in WSNs?
152(2)
5.2.2 Key Ideas
154(4)
5.2.3 Protocol Description
158(5)
5.2.3.1 Pump Operation
159(1)
5.2.3.2 Fetch Operation
160(2)
5.2.3.3 Report Operation
162(1)
5.3 Another WSN Transport Protocol—ESRT
163(8)
5.3.1 Reliable Transport Problem
163(1)
5.3.2 Relationship between Normalized Event Reliability and Report Frequency
164(6)
5.3.3 Congestion Detection
170(1)
5.4 E2SRT: Enhanced 'ESRT Performance
171(7)
5.4.1 The Proposed Scheme—E2SRT
173(5)
5.5 CODA: Congestion Detection and Avoidance in Sensor Networks
178(7)
5.5.1 Open-Loop, Hop-to-Hop Backpressure
182(1)
5.5.2 Congestion Detection
183(1)
5.5.3 Listening to Channel Based on Sampling
183(2)
5.6 STCP: A Generic Transport Layer Protocol for WSNs
185(4)
5.6.1 Data Transmission Sequence in STCP
185(1)
5.6.2 STCP Packet Formats
185(2)
5.6.3 Continuous Flows
187(1)
5.6.4 Event-Driven Flows
188(1)
5.6.5 Reliability
188(1)
5.6.6 Congestion Detection and Avoidance
188(1)
5.6.7 Data-Centric Applications
189(1)
5.7 GARUDA: Achieving Effective Reliability for Downstream Communication
189(7)
5.7.1 Challenges to the Downstream Reliability of WSNs
190(1)
5.7.1.1 Environment Constraints
190(1)
5.7.1.2 Acknowledgment (ACK)/NACK Paradox
190(1)
5.7.1.3 Reliability Semantics
190(1)
5.7.2 GARUDA Design Basics
191(2)
5.7.2.1 Loss Recovery Servers: Core
191(1)
5.7.2.2 Loss Recovery Process
192(1)
5.7.3 GARUDA Framework
193(8)
5.7.3.1 Core Construction Procedure
194(1)
5.7.3.2 Two-Phase Loss Recovery
195(1)
Problems and Exercises
196(5)
PART IV COMPUTER SCIENCE PRINCIPLES
6 Operating System in Sensors
201(24)
6.1 TinyOS
201(8)
6.1.1 Overview
202(1)
6.1.2 Component Model
203(3)
6.1.3 Execution Model and Concurrency
206(2)
6.1.4 Active Messages
208(1)
6.1.5 Implementation Status
208(1)
6.1.6 Main Features
208(1)
6.1.7 Low-Power Optimizations
209(1)
6.2 LA-TinyOS—A Locality-Aware Operating System for WSNs
209(6)
6.2.1 Change Timer to Respond to Temporal and Spatial Locality
211(2)
6.2.2 Multiple-Level Scheduler
213(1)
6.2.3 LA-TinyOS Code Structure
214(1)
6.3 SOS
215(4)
6.3.1 Modules
216(3)
6.3.1.1 Module Structure
216(1)
6.3.1.2 Module Interaction
217(1)
6.3.1.3 Module Insertion and Removal
217(2)
6.3.2 Dynamic Memory
219(1)
6.4 RETOS
219(4)
6.4.1 Application Code Checking
219(2)
6.4.2 Multithreading System
221(1)
6.4.3 Loadable Kernel Module
222(1)
Problems and Exercises
223(2)
7 Middleware Design in Wireless Sensor Networks
225(12)
7.1 Introduction
225(2)
7.2 Reference Model of WSN Middleware
227(1)
7.2.1 Model Overview
227(1)
7.3 Middleware Example: Agilla
228(3)
7.4 Middleware for Data Acquisition: Mires
231(2)
7.5 Data Storage: DSWare
233(1)
7.6 WSN Runtime Support Example: Mate
234(1)
7.7 QoS Support Example: MiLAN
235(1)
Problems and Exercises
236(1)
8 Sensor Data Management.
237(24)
8.1 Sensor Data Cleaning
237(6)
8.1.1 Background
237(2)
8.1.2 General Model
239(2)
8.1.3 Reducing the Uncertainty
241(2)
8.2 TinyDB: An Acquisitional Query-Processing System for Sensor Networks
243(6)
8.2.1 Data Model
245(1)
8.2.2 Basic Language Features
245(1)
8.2.3 Event-Based Queries
246(1)
8.2.4 Other Queries Defined in TinyDB
246(1)
8.2.5 Power-Based Query Optimization
247(2)
8.2.6 Summary of TinyDB Strategies
249(1)
8.3 Data Aggregation: AIDA
249(4)
8.4 Sensor Data Storage: Tiered Storage ARchitecture (TSAR)
253(3)
8.5 Multi-Resolution Data Processing
256(1)
Problems and Exercises
257(4)
PART V ADVANCED TOPICS
9 Sensor Localization
261(46)
9.1 Introduction
261(1)
9.2 Elements of Localization
262(6)
9.2.1 Received Signal Strength Indication
262(2)
9.2.2 Time of Arrival
264(1)
9.2.3 Time Difference of Arrival
264(2)
9.2.4 Angle of Arrival
266(1)
9.2.5 Triangulation
266(1)
9.2.6 Trilateration
266(1)
9.2.7 Multilateration
267(1)
9.3 Using Mobile Robots for Sensor Localization
268(6)
9.3.1 Delay-Tolerant Sensor Networks
268(6)
9.3.1.1 System Dynamic Model
269(2)
9.3.1.2 RSSI Measurement Model
271(3)
9.4 Sensor Localization with Multidimensional Scaling
274(6)
9.4.1 Classical Multidimensional Scaling
274(1)
9.4.2 Iterative Multidimensional Scaling
275(5)
9.4.2.1 Hop Distance and Ranging Estimation
276(1)
9.4.2.2 Aligning Relative Location to Physical Location
276(2)
9.4.2.3 Distributed Physical Location Estimation
278(2)
9.5 Localization in Wireless Sensor Networks
280(5)
9.5.1 The Monte Carlo Method
280(1)
9.5.2 Algorithm (1)
281(3)
9.5.3 Algorithm (2)
284(1)
9.6 GPS-Free Node Localization in Mobile WSN
285(5)
9.7 A High-Accuracy, Low-Cost Localization System for WSN
290(5)
9.8 LOCALE: Collaborative Localization Estimation for Sparse Mobile Sensor Networks
295(8)
9.8.1 Collaborative Location Estimation
296(1)
9.8.2 Location in LOCALE
297(1)
9.8.3 Local Phase
297(2)
9.8.4 Transform Phase
299(2)
9.8.5 Update Phase
301(2)
9.9 On the Security of WSN Localization
303(2)
9.9.1 SeRLoc
303(1)
9.9.2 Beacon Suite
304(1)
9.9.3 Attack-Resistant Location Estimation
304(1)
9.9.4 Robust Statistical Methods
305(1)
Problems and Exercises
305(2)
10 Time Synchronization in Wireless Sensor Networks
307(20)
10.1 Introduction
307(4)
10.2 Synchronization in General Networks (Non-WSN)
311(3)
10.2.1 Remote Clock Reading
311(1)
10.2.2 Offset Delay Estimation Method
311(3)
10.3 Clock Synchronization in WSNs
314(3)
10.4 Evaluation of Synchronization Performance
317(2)
10.4.1 Precision
317(1)
10.4.2 Protocol Overhead
318(1)
10.4.3 Convergence Time
318(1)
10.4.4 Energy Efficiency
318(1)
10.4.5 Scalability
318(1)
10.4.6 Robustness
318(1)
10.5 Examples of WSN Synchronization Protocols
319(6)
10.5.1 Reference Broadcast Synchronization
319(2)
10.5.2 Time-Diffusion Synchronization Protocol
321(3)
10.5.3 Probabilistic Clock Synchronization
324(1)
Problems and Exercises
325(2)
11 Security and Privacy in Wireless Sensor Networks
327(36)
11.1 Introduction
327(9)
11.1.1 General Attack Taxonomy
327(1)
11.1.2 Attacks on Physical Sensor Motes
328(2)
11.1.3 Attacks on WSN Communication Stack
330(6)
11.1.3.1 Physical Layer
330(1)
11.1.3.2 Link Layer
330(1)
11.1.3.3 Routing Layer
331(4)
11.1.3.4 Transport Layer
335(1)
11.1.3.5 Traffic Analysis Attacks
335(1)
11.2 Attack and Countermeasure Example: Wormhole Attack
336(8)
11.2.1 Wormhole Defense Schema-LITEWORP
336(11)
11.2.1.1 Building Neighbor Lists
340(4)
11.3 WSN Security Example: Blom-Based Approach
344(3)
11.4 Broadcast Authentication: μTESLA
347(5)
11.4.1 μTESLA's Detailed Description
350(2)
11.5 Practical Security Schemes for "Motes"
352(2)
11.5.1 TinySec
352(1)
11.5.2 MiniSec: A Secure Sensor Network Communication Architecture
353(1)
11.6 Special Case: Secure Time Synchronization in WSNs
354(5)
Problems and Exercises
359(4)
PART VI SPECIAL WIRELESS SENSOR NETWORKS
12 Wireless Sensor and Actor Networks.
363(16)
12.1 Introduction
363(3)
12.2 Sensor–Actor Coordination Problem
366(7)
12.2.1 Network and Energy Model
367(1)
12.2.2 ILP Algorithm
367(3)
12.2.3 Sensor–Actor Coordination: Distributed Protocol
370(1)
12.2.4 Overview of DEPR
371(2)
12.3 Hierarchical Sensor–Actor Coordination Mechanism
373(5)
12.3.1 Hierarchical WSAN Coordination Architecture
373(1)
12.3.2 "Sensor–Sensor" Coordination Level—Use Clusters
374(2)
12.3.3 "Sensor–Actor" Coordination Level
376(1)
12.3.4 "Actor–Actor" Coordination Level
377(1)
Problems and Exercises
378(1)
13 Underwater Sensor Networks
379(20)
13.1 Introduction
379(5)
13.1.1 Underwater WSN Applications
379(1)
13.1.2 Differences between USNs and Terrestrial Sensor Networks
380(1)
13.1.3 Network Topology
381(1)
13.1.4 Acoustic Signals Propagation
382(1)
13.1.5 Underwater Sensors
383(1)
13.2 USN Protocol Stack
384(3)
13.2.1 Physical Layer
384(1)
13.2.2 Data Link Layer
385(1)
13.2.3 Network Layer (Routing Layer)
386(1)
13.2.4 Transport Layer
386(1)
13.3 MAC Design Example
387(3)
13.4 Routing Design Example: Vector-Based Forwarding Protocol
390(3)
13.5 Hardware Prototype Design
393(5)
13.5.1 Hardware Design
394(2)
13.5.2 Software Design
396(1)
13.5.3 System Testing
396(2)
Problems and Exercises
398(1)
14 Video Sensor Networks
399(16)
14.1 Introduction
399(2)
14.2 Panoptes
401(2)
14.2.1 Video Capture
402(1)
14.2.2 Video Compression
402(1)
14.2.3 Data Filtering
402(1)
14.2.4 Data Buffering
402(1)
14.3 Cyclops
403(2)
14.4 VSN Calibration
405(3)
14.4.1 Determining the Degree of Overlap
407(1)
14.4.2 Estimating k-overlap
407(1)
14.5 SensEye
408(4)
Problems and Exercises
412(3)
PART VII MISCELLANEOUS TOPICS
15 WSN Energy Model
415(16)
15.1 Basic WSN Energy Model
415(3)
15.2 Simulation-Based Energy Modeling
418(7)
15.3 Battery-Aware Routing
425(4)
Problems and Exercises
429(2)
16 Sensor Network Simulators
431(14)
16.1 GloMoSim
431(1)
16.2 SensorSim
432(2)
16.3 TOSSIM
434(3)
16.4 PowerTOSSIM
437(4)
16.4.1 PowerTOSSIM Architecture
437(2)
16.4.2 Component Instrumentation
439(1)
16.4.3 CPU Profiling
439(1)
16.4.4 PowerState Module
440(1)
16.4.5 Analysis Tools
440(1)
Problems and Exercises
441(4)
PART VIII CASE STUDIES
17 Case Study 1: Tele-Healthcare
445(20)
17.1 Introduction
445(2)
17.2 MASN Hardware Design
447(3)
17.2.1 ECG Sensors and RF Communication Hardware
447(3)
17.3 Reliable MASN Communication Protocols
450(5)
17.3.1 Enhanced Cluster-Based MASN Data Transmission
450(3)
17.3.2 MASN Routing Performance
453(2)
17.4 MASN Software Design
455(2)
17.4.1 ECG Sensor Mote Wireless Communication Software
455(2)
17.5 Integration of RFID and Wearable Sensors
457(5)
Problems and Exercises
462(3)
18 Case Study 2: Light Control
465(10)
18.1 Introduction
465(3)
18.2 Illumimote's Sensors
468(1)
18.3 System Architecture
469(1)
18.4 Calibration
469(1)
18.5 System Evaluation
470(2)
Problems and Exercises
472(3)
References 475(20)
Index 495
Dr. Fei Hu is an associate professor in the Department of Electrical and Computer Engineering of the University of Alabama, Tuscaloosa, USA. His research interests include sensor networks, wireless networks, network security and their application to Bio-Medicine. His research has been supported by U.S. NSF, Cisco, Sprint, and other sources. He obtained his Ph.D. degrees at Tongji University, Shanghai, China, in the field of Signal Processing, and at Clarkson University, New York, USA, in the field of Electrical and Computer Engineering. He holds M.S. and B.S. degrees in Telecommunication Engineering from Shanghai Tiedao University and has published over 100 journal/conference papers and book chapters.

Dr. Xiaojun Cao is an assistant professor in the Computer Science Department of Georgia State University. He received his Ph.D. degree in Computer Science and Engineering from the State University of New York at Buffalo. Dr. Cao's research has been sponsored by U.S. National Science Foundation (NSF), IBM and Cisco's University Research Program. He is a recipient of the NSF CAREER Award, 2006-2011. Dr. Cao is working on modeling, analysis, and protocols/algorithms design of communication networks. Important among these are Optical Networking, Waveband Switching, Optical Burst Switching, Mobile Ad hoc Networks, Sensor Networks and Security, and Optical Wireless Communications.He holds a B.S. degree from Tsinghua University as well as a M.S. from the Chinese Academy of Sciences.
Pastovi nuoroda: https://www.kriso.lt/db/9780429111488_pe.html
Raktažodžiai: